Lens Performance

I have a friend – yes, a strange concept I know, but I do have some – we’ll call him Steve.

Steve is a very talented photographer – when he’ll give himself half a chance; but impatience can sometimes get the better of him.

He’ll have a great scene in front of him but then he’ll forget things such as any focus or exposure considerations the scene demands, and the resulting image will be crap!

Quite often, a few of Steve’s character flaws begin to emerge at this juncture.

Firstly, Steve only remembers his successes; this leads to the unassailable ‘fact’ that he couldn’t possibly have ‘screwed up’.

So now we can all guess the conclusive outcome of that scenario can’t we……..that’s right; his camera gear has fallen short in the performance department.

Clairvoyance department would actually be more accurate!

So this ‘error in his camera system’ needs to be stamped on – hard and fast!

This leads to Steve embarking on a massive information-gathering exercise from various learned sources on ‘that there inter web’ – where another of Steve’s flaws shows up; that of disjointed speed reading…..

The terrifying outcome of these situations usually concludes with Steve’s confident affirmation that some piece of his equipment has let him down; not just by becoming faulty but sometimes, more worryingly by initial design.

These conclusions are always arrived at in the same manner – the various little snippets of truth and random dis-associated facts that Steve gathers, all get forcibly hammered into some hellish, bastardized ‘factual’ jigsaw in his head.

There was a time when Steve used to ask me first, but he gave up on that because my usual answer contravened the outcome of his first mentioned character flaw!

Lately one of Steve’s biggest peeves has been the performance of one or two of his various lenses.

Ostensibly you’ll perhaps think there’s nothing wrong in that – after all, the image generated by the camera is only as good as the lens used to gather the light in the scene – isn’t it?

 

But there’s a potential problem, and it  lies in what evidence you base your conclusions on……………

 

For Steve, at present, it’s manufacturers MTF charts, and comparisons thereof, coupled with his own images as they appear in Lightroom or Photoshop ACR.

Again, this might sound like a logical methodology – but it isn’t.

It’s flawed on so many levels.

 

The Image Path from Lens to Sensor

We could think of the path that light travels along in order to get to our camera sensor as a sort of Grand National horse race – a steeplechase for photons!

“They’re under starters orders ladies and gentlemen………………and they’re off!”

As light enters the lens it comes across it’s first set of hurdles – the various lens elements and element groups that it has to pass through.

Then they arrive at Becher’s Brook – the aperture, where there are many fallers.

Carefully staying clear of the inside rail and being watchful of any lose photons that have unseated their riders at Becher’s we move on over Foinavon – the rear lens elements, and we then arrive at the infamous Canal Turn – the Optical Low Pass filter; also known as the Anti-alias filter.

Crashing on past the low pass filter and on over Valentines only the bravest photons are left to tackle the the last big fence on their journey – The Chair – our camera sensor itself.

 

Okay, I’ll behave myself now, but you get the general idea – any obstacle that lies in the path of light between the front surface of our lens and the photo-voltaic surface of our sensor is a BAD thing.

Andy Astbury,Wildlife in Pixels,lens,resolution,optical path,sharpness,resolution,imaging pathway

The various obstacles to light as it passes through a camera (ASIC = Application Specific Integrated Circuit)

The problems are many, but let’s list a few:

  1. Every element reduces the level of transmitted light.
  2. Because the lens elements have curved surfaces, light is refracted or bent; the trick is to make all wavelengths of light refract to the same degree – failure results in either lateral or longitudinal chromatic aberration – or worse still, both.
  3. The aperture causes diffraction – already discussed HERE

We have already seen in that same previous post on Sensor Resolution that the number of megapixels can effect overall image quality in terms of overall perceived sharpness due to pixel-pitch, so all things considered, using photographs of any 3 dimensional scene is not always a wise method of judging lens performance.

And here is another reason why it’s not a good idea – the effect on image quality/perceived lens resolution of anti-alias, moire or optical low pass filter; and any other pre-filtering.

I’m not going to delve into the functional whys and wherefores of an AA filter, save to say that it’s deemed a necessary evil on most sensors, and that it can make your images take on a certain softness because it basically adds blur to every edge in the image projected by the lens onto your sensor.

The reasoning behind it is that it stops ‘moire patterning’ in areas of high frequency repeated detail.  This it does, but what about the areas in the image where its effect is not required – TOUGH!

 

Many photographers have paid service suppliers for AA filter removal just to squeeze the last bit of sharpness out of their sensors, and Nikon of course offer the ‘sort of AA filter-less’ D800E.

Side bar note:  I’ve always found that with Nikon cameras at least, the pro-body range seem to suffer a lot less from undesirable AA filtration softening than than their “amateur” and “semi pro” bodies – most notably the D2X compared to a D200, and the D3 compared to the D700 & D300.  Perhaps this is due to a ‘thinner’ filter, or a higher quality filter – I don’t know, and to be honest I’ve never had the desire to ‘poke Nikon with a sharp stick’ in order to find out.

 

Back in the days of film things were really simple – image resolution was governed by just two things; lens resolution and film resolution:

1/image resolution = 1/lens resolution + 1/film resolution

Film resolution was a variable depending on the Ag Halide distribution and structure,  dye coupler efficacy within the film emulsion, and the thickness of the emulsion or tri-pack itself.

But today things are far more complicated.

With digital photography we have all those extra hurdles to jump over that I mentioned earlier, so we end up with a situation whereby:

1/Image Resolution = 1/lens resolution + 1/AA filter resolution + 1/sensor resolution + 1/image processor/imaging ASIC resolution

Steve is chasing after lens resolution under the slightly misguided idea the resolution equates to sharpness, which is not strictly true; but he is basing his conception of lens sharpness based on the detail content and perceived detail ‘sharpness’ of his  images; which are ‘polluted’ if you like by the effects of the AA filter, sensor and imaging ASIC.

What it boils down to, in very simplified terms, is this:

You can have one particular lens that, in combination with one camera sensor produces a superb image, but in combination with another sensor produces a not-quite-so-superb image!

On top of the “fixed system” hurdles I’ve outlined above, we must not forget the potential for errors introduced by lens-to-body mount flange inaccuracies, and of course, the big elephant-in-the-room – operator error – ehh Steve.

So attempting to quantify the pure ‘optical performance’ of a lens using your ‘taken images’ is something of a pointless exercise; you cannot see the pure lens sharpness or resolution unless you put the lens on a fully equipped optical test bench – and how many of us have got access to one of those?

The truth of the matter is that the average photographer has to trust the manufacturers to supply accurately put together equipment, and he or she has to assume that all is well inside the box they’ve just purchased from their photographic supplier.

But how can we judge a lens against an assumed standard of perfection before we part with our cash?

A lot of folk, including Steve – look at MTF charts.

 

The MTF Chart

Firstly, MTF stands for Modulation Transfer Function – modu-what I hear your ask!

OK – let’s deal with the modulation bit.  Forget colour for a minute and consider yourself living in a black & white world.  Dark objects in a scene reflect few photons of light – ’tis why the appear dark!  Conversely, bright objects reflect loads of the little buggers, hence these objects appear bright.

Imagine now that we are in a sealed room totally impervious to the ingress of any light from outside, and that the room is painted matte white from floor to ceiling – what is the perceived colour of the room? Black is the answer you are looking for!

Now turn on that 2 million candle-power 6500k searchlight in the corner.  The split second before your retinas melted, what was the perceived colour of the room?

Note the use of the word ‘perceived’ – the actual colour never changed!

The luminosity value of every surface in the room changed from black to white/dark to bright – the luminosity values MODULATED.

Now back in reality we can say that a set of alternating black and white lines of equal width and crisp clean edges represent a high degree of contrast, and therefore tonal modulation; and the finer the lines the higher is the modulation frequency – which we measure in lines per millimeter (lpmm).

A lens takes in a scene of these alternating black and white lines and, just like it does with any other scene, projects it into an image circle; in other words it takes what it sees in front of it and ‘transfers’ the scene to the image circle behind it.

With a bit of luck and a fair wind this image circle is being projected sharply into the focal plane of the lens, and hopefully the focal plane matches up perfectly with the plane of the sensor – what used to be refereed to as the film plane.

The efficacy with which the lens carries out this ‘transfer’ in terms of maintaining both the contrast ratio of the modulated tones and the spatial separation of the lines is its transfer function.

So now you know what MTF stands for and what it means – good this isn’t it!

 

Let’s look at an MTF chart:

Nikon 500mm f4 MTF chart

Nikon 500mm f4 MTF chart

Now what does all this mean?

 

Firstly, the vertical axis – this can be regarded as that ‘efficacy’ I mentioned above – the accuracy of tonal contrast and separation reproduction in the projected image; 1.0 would be perfect, and 0 would be crappier than the crappiest version of a crap thing!

The horizontal axis – this requires a bit of brain power! It is scaled in increments of 5 millimeters from the lens axis AT THE FOCAL PLANE.

The terminus value at the right hand end of the axis is unmarked, but equates to 21.63mm – half the opposing corner-to-corner dimension of a 35mm frame.

Now consider the diagram below:

Andy Astbury,image circle,photography,frame,full frame,dimensions,radial,

The radial dimensions of the 35mm format.

These are the radial dimensions, in millimeters, of a 35mm format frame (solid black rectangle).

The lens axis passes through the center axis of the sensor, so the radii of the green, yellow and dashed circles correspond to values along the horizontal axis of an MTF chart.

Let’s simplify what we’ve learned about MTF axes:

Andy Astbury,image circle,photography,frame,full frame,dimensions,radial,

MTF axes hopefully made simpler!

Now we come to the information data plots; firstly the meaning of Sagittal & Meridional.   From our perspective in this instance I find it easier for folk to think of them as ‘parallel to’ and ‘at right angles to’ the axis of measurement, though strictly speaking Meridional is circular and Sagittal is radial.

This axis of measurement is from the lens/film plane/sensor center to the corner of a 35mm frame – in other words, along that 21.63mm radius.

Andy Astbury,image circle,photography,frame,full frame,dimensions,radial,

The axis of MTF measurement and the relative axial orientation of Sagittal & Meridional lines. NOTE: the target lines are ONLY for illustration.

Separate measurements are taken for each modulation frequency along the entire measurement axis:

Andy Astbury,image circle,photography,frame,full frame,dimensions,radial,

Thin Meridional MTF measurement. (They should be concentric circles but I can’t draw concentric circles!).

Let’s look at that MTF curve for the 500m f4 Nikon together with a legend of ‘sharpness’ – the 300 f2.8:

MTF chart,Andy Astbury,lens resolution

Nikon MTF comparison between the 500mm f4 & 300mm f2.8

Nikon say on their website that they measure MTF at maximum aperture, that is, wide open; so the 300mm chart is for an aperture of f2.8 (though they don’t say so) and the 500mm is for an f4 aperture – which they do specify on the chart – don’t ask me why ‘cos I’ve no idea.

As we can see, the best transfer values for the two lenses (and all other lenses) is 10 lines per millimeter, and generally speaking sagittal orientation usually performs slightly better than meridional, but not always.

10 lpmm is always going to give a good transfer value because its very coarse and represents a lower frequency of detail than 30 lpmm.

Funny thing, 10 lines per millimeter is 5 line pairs per millimeter – and where have we heard that before? HERE – it’s the resolution of the human eye at 25 centimeters.

 

Another interesting thing to bare in mind is that, as the charts clearly show, better transfer values occur closer to the lens axis/sensor center, and that performance falls as you get closer to the frame corners.

This is simply down to the fact that your are getting closer to the inner edge of the image circle (the dotted line in the diagrams above).  If manufacturers made lenses that threw a larger image circle then corner MTF performance would increase – it can be done – that’s the basis upon which PCE/TS lenses work.

One way to take advantage of center MTF performance is to use a cropped sensor – I still use my trusty D2Xs for a lot of macro work; not only do I get the benefit of center MTF performance across the majority of the frame but I also have the ability to increase the lens to subject distance and get the composition I want, so my depth of field increases slightly for any given aperture.

Back to the matter at hand, here’s my first problem with the likes of Nikon, Canon etc:  they don’t specify the lens-to-target distance. A lens that gives a transfer value of 9o% plus on a target of 10 lpmm sagittal at 2 meters distance is one thing; one that did the same but at 25 meters would be something else again.

You might look at the MTF chart above and think that the 300mm f2.8 lens is poor on a target resolution of  30 lines per millimeter compared to the 500mm, but we need to temper that conclusion with a few facts:

  1. A 300mm lens is a lot wider in Field of View (FoV) than a 500mm so there is a lot more ‘scene width’ being pushed through the lens – detail is ‘less magnified’.
  2. How much ‘less magnified’ –  40% less than at 500mm, and yet the 30 lpmm transfer value is within 6% to 7% that of the 500mm – overall a seemingly much better lens in MTF terms.
  3. The lens is f2.8 – great for letting light in but rubbish for everything else!

Most conventional lenses have one thing in common – their best working aperture for overall image quality is around f8.

But we have to counter balance the above with the lack of aforementioned target distance information.  The minimum focus distances for the two comparison lenses are 2.3 meters and 4.0 meters respectively so obviously we know that the targets are imaged and measured at vastly different distances – but without factual knowledge of the testing distances we cannot really say that one lens is better than the other.

 

My next problem with most manufacturers MTF charts is that the values are supplied ‘a la white light’.

I mentioned earlier – much earlier! – that lens elements refracted light, and the importance of all wavelengths being refracted to the same degree, otherwise we end up with either lateral or longitudinal chromatic aberration – or worse still – both!

Longitudinal CA will give us different focal planes for different colours contained within white light – NOT GOOD!

Lateral CA gives us the same plane of focus but this time we get lateral shifts in the red, green and blue components of the image, as if the 3 colour channels have come out of register – again NOT GOOD!

Both CA types are most commonly seen along defined edges of colour and/or tone, and as such they both effect transferred edge definition and detail.

So why do manufacturers NOT publish this information – there is to my knowledge only one that does – Schneider (read ‘proper lens’).

They produce some very meaningful MTF data for their lenses with modulation frequencies in excess of 90 to 150 lpmm; separate R,G & B curves; spectral weighting variations for different colour temperatures of light and all sorts of other ‘geeky goodies’ – I just love it all!

 

SHAME ON YOU NIKON – and that goes for Canon and Sigma just as much.

 

So you might now be asking WHY they don’t publish the data – they must have it – are they treating us like fools that wouldn’t be able to understand it; OR – are they trying to hide something?

You guys think what you will – I’m not accusing anyone of anything here.

But if they are trying to hide something then that ‘something’ might not be what you guys are thinking.

What would you think if I told you that if you were a lens designer you could produce an MTF plot with a calculator – ‘cos you can, and they do!

So, in a nutshell, most manufacturers MTF charts as published for us to see are worse than useless.  We can’t effectively use them to compare one lens against another because of missing data; we can’t get an idea of CA performance because of missing red, green and blue MTF curves; and finally we can’t even trust that the bit of data they do impart is even bloody genuine.

Please don’t get taken in by them next time you fancy spending money on glass – take your time and ask around – better still try one; and try it on more than 1 camera body!

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Sensor Resolution

Sensor Resolution

In my previous two posts on this subject HERE and HERE I’ve been looking at pixel resolution as it pertains to digital display and print, and the basics of how we can manipulate it to our benefit.

You should also by aware by now that I’m not the worlds biggest fan of high sensor resolution 35mm format dSLRs – there’s nothing wrong with mega pixels; you can’t have enough of them in my book!

BUT, there’s a limit to how many you can cram into a 36 x 24 millimeter sensor area before things start getting silly and your photographic life gets harder.

So in this post I want to explain the reasoning behind my thoughts.

But before I get into that I want to address something else to do with resolution – the standard by which we judge everything we see around us – the resolution of the eye.

 

Human Eye – How Much Can We See?

In very simple terms, because I’m not an optician, the answer goes like this.

Someone with what some call 20/20/20 vision – 20/20 vision in a 20 year old – has a visual acuity of 5 line pairs per millimeter at a distance of 25 centimeters.

What’s a line pair?

5 line pairs per millimeter. Each line pair is 0.2mm and each line is 0.1mm.

5 line pairs per millimeter. Each line pair is 0.2mm and each line is 0.1mm.

Under ideal viewing conditions in terms of brightness and contrast the human eye can at best resolve 0.1mm detail at a distance of 25 centimeters.

Drop the brightness and the contrast and black will become less black and more grey, and white will become greyer; the contrast between light and dark becomes reduced and therefore that 0.1mm detail becomes less distinct.  until the point comes where the same eye can’t resolve detail any smaller than 0.2mm at 25cms, and so on.

Now if I try and focus on something at 25 cms my eyeballs start to ache,  so we are talking extreme close focus for the eye here.

An interesting side note is that 0.1mm is 100µm (microns) and microns are what we measure the size of sensor photosites in – which brings me nicely to SENSOR resolution.

 

Sensor Resolution – Too Many Megapixels?

As we saw in the post on NOISE we do not give ourselves the best chances by employing sensors with small photosite diameters.  It’s a basic fact of physics and mathematics – the more megapixels on a sensor, then the smaller each photosite has to be in order to fit them all in there;  and the smaller they are then the lower is their individual signal to noise or S/N ratio.

But there is another problem that comes with increased sensor resolution:

Increased diffraction threshold.

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Schematic of identical surface areas on lower and higher megapixel sensors.

In the above schematic we are looking at the same sized tiny surface area section on two sensors.

If we say that the sensor resolution on the left is that of a 12Mp Nikon D3, and the ‘area’ contains 3 x 3 photosites which are each 8.4 µm in size, then we can say we are looking at an area of about 25µm square.

On the right we are looking at that same 25µm (25 micron) square, but now it contains 5.2 x 5.2 photosites, each 4.84µm in size – a bit like the sensor resolution of a 36Mp D800.

 

What is Diffraction?

Diffraction is basically the bending or reflecting of waves by objects placed in their path (not to be confused with refraction).  As it pertains to our camera sensor, and overall image quality, it causes an general softening of every single point of sharp detail in the image that is projected onto the sensor during the exposure.

I say during the exposure because diffraction is ‘aperture driven’ and it’s effects only occur when the aperture is ‘stopped down’; which on modern cameras only occurs during the time the shutter is open.

At all other times you are viewing the image with the aperture wide open, and so you can’t see the effect unless you hit the stop down button (if you have one) and even then the image in the viewfinder is so small and dark you can’t see it.

As I said, diffraction is caused by aperture diameter – the size of the hole that lets the light in:

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Diffraction has a low presence in the system at wider apertures.

Light enters the lens, passes through the aperture and strikes the focal plane/sensor causing the image to be recorded.

Light waves passing through the center of the aperture and light waves passing through the periphery of the aperture all need to travel the same distance – the focal distance – in order for the image to be sharp.

The potential for the peripheral waves to be bent by the edge of the aperture diaphragm increases as the aperture becomes smaller.

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Diffraction has a greater presence in the system at narrower apertures.

If I apply some randomly chosen numbers to this you might understand it a little better:

Let’s say that the focal distance of the lens (not focal length) is 21.25mm.

As long as light passing through all points of the aperture travels 21.25mm and strikes the sensor then the image will be sharp; in other words, the more parallel the central and peripheral light waves are, then the sharper the image.

Making the aperture narrower by ‘stopping down’ increases the divergence between central and peripheral waves.

This means that peripheral waves have to travel further before the strike the sensor; further than 21.25mm – therefore they are no longer in focus, but those central waves still are.  This effect gives a fuzzy halo to every single sharply focused point of light striking our sensor.

Please remember, the numbers I’ve used above are meaningless and random.

The amount of fuzziness varies with aperture – wider aperture =  less fuzzy; narrower aperture = more fuzzy, and the circular image produced by a single point of sharp focus is known as an Airy Disc.

As we ‘stop down’ the aperture the edges of the Airy Disc become softer and more fuzzy.

Say for example, we stick a 24mm lens on our camera and frame up a nice landscape, and we need to use f14 to generate the amount of depth of field we need for the shot.  The particular lens we are using produces an Airy Disc of a very particular size at any given aperture.

Now here is the problem:

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Schematic of identical surface areas on lower and higher megapixel sensors and the same diameter Airy Disc projected on both of them.

As you can see, the camera with the lower sensor resolution and larger photosite diameter contains the Airy Disc within the footprint of ONE photosite; but the disc effects NINE photosites on the camera with the higher sensor resolution.

Individual photosites basically record one single flat tone which is the average of what they see; so the net outcome of the above scenario is:

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Schematic illustrating the tonal output effect of a particular size Airy Disc on higher and lower resolution sensors

On the higher resolution sensor the Airy Disc has produced what we might think of as ‘response pollution’ in the 8 surrounding photosites – these photosites need to record the values of the own ‘bits of the image jigsaw’ as well – so you end up with a situation where each photosite on the sensor ends up recording somewhat imprecise tonal values – this is diffraction in action.

If we were to stop down to f22 or f32 on the lower resolution sensor then the same thing would occur.

If we used an aperture wide enough on the higher resolution sensor – an aperture that generated an Airy Disc that was the same size or smaller than the diameter of the photosites – then only 1 single photosite would be effected and diffraction would not occur.

But that would leave of with a reduced depth of field – getting around that problem is fairly easy if you are prepared to invest in something like a Tilt-Shift lens.

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Both images shot with a 24mm TS lens at f3.5. Left image lens is set to zero and behaves as normal 24mm lens. Right image has 1 degree of down tilt applied.

Above we see two images shot with a 24mm Tilt-Shift lens, and both shots are at f3.5 – a wide open aperture.  In the left hand image the lens controls are set to zero and so it behaves like a standard construction lens of 24mm and gives the shallow depth of field that you’d expect.

The image on the right is again, shot wide open at f3.5, but this time the lens was tilted down by just 1 degree – now we have depth of field reaching all the way through the image.  All we would need to do now is stop the lens down to its sharpest aperture – around f8 – and take the shot;  and no worries about diffraction.

Getting back to sensor resolution in general, if your move into high megapixels counts on 35mm format then you are in a ‘Catch 22’ situation:

  • Greater sensor resolution enables you to theoretically capture greater levels of detail.

but that extra level of detail is somewhat problematic because:

  • Diffraction renders it ‘soft’.
  • Eliminating the diffraction causes you to potentially lose the newly acquired level of, say foreground detail in a landscape, due to lack of depth of field.

All digital sensors are susceptible to diffraction at some point or other – they are ‘diffraction limited’.

Over the years I’ve owned a Nikon D3 I’ve found it diffraction limited to between f16 & f18 – I can see it at f18 but can easily rescue the situation.  When I first used a 24Mp D3X I forgot what I was using and spent a whole afternoon shooting at f16 & f18 – I had to go back the next day for a re-shoot because the sensor is diffraction limited to f11 – the pictures certainly told the story!

Everything in photography is a trade-off – you can’t have more of one thing without having less of another.  Back in the days of film we could get by with one camera and use different films because they had very different performance values, but now we buy a camera and expect its sensor to perform all tasks with equal dexterity – sadly, this is not the case.  All modern consumer sensors are jacks of all trades.

If it’s sensor resolution you want then by far the best way to go about it is to jump to medium format, if you want image quality of the n’th degree – this way you get the ‘pixel resolution’ without many of the incumbent problems I’ve mentioned, simply because the sensors are twice the size; or invest in a TS/PC lens and take the Scheimpflug route to more depth of field at a wider aperture.

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Noise and the Camera Sensor

Camera sensors all suffer with two major afflictions; diffraction and noise; and between them these two afflictions cause more consternation amongst photographers than anything else.

In this post I’m going to concentrate on NOISE, that most feared of sensor afflictions, and its biggest influencer – LIGHT, and its properties.

What Is Light?

As humans we perceive light as being a constant continuous stream or flow of electromagnetic energy, but it isn’t!   Instead of flowing like water it behaves more like rain, or indeed, bullets from a machine gun!   Here’s a very basic physics lesson:

Below is a diagram showing the Bohr atomic model.

We have a single positively charged proton (black) forming the nucleus, and a single negatively charged electron (green) orbiting the nucleus.

The orbit distance n1 is defined by the electrostatic balance of the two opposing charges.

Andy Astbury,noise,light,Bohr atomic model

The Bohr Atomic Model

If we apply energy to the system then a ‘tipping point’ is reached and the electron is forced to move away from the nucleus – n2.

Apply even more energy and the system tips again and the electron is forced to move to an even higher energy level – n3.

Now here’s the fun bit – stop applying energy to the system.

As the system is no longer needing to cope with the excess energy it returns to its natural ‘ground’ state and the electron falls back to n1.

In the process the electron sheds the energy it has absorbed – the red squiggly bit – as a quantum, or packet, of electromagnetic energy.

This is basically how a flash gun works.

This ‘packet’ has a start and an end; the start happens as the electron begins its fall back to its ground state; and the end occurs once the electron arrives at n1 – therefore it can perhaps be tentatively thought of as being particulate in nature.

So now you know what Prof. Brian Cox knows – CERN here we come!

Right, so what’s this got to do with photography and camera sensor noise

Camera Sensor Noise

All camera sensors are effected by noise, and this noise comes in various guises:

Firstly, the ‘noise control’ sections of most processing software we use tend to break it down into two components; luminosity, or luminance noise; and colour noise.  Below is a rather crappy image that I’m using to illustrate what we might assume is the reality of noise:

Andy Astbury,noise

This shot shows both Colour & Luminance noise.
The insert shows the shot and the small white rectangle is the area we’re concentrating on.

Now let’s look at the two basic components: Firstly the LUMINANCE component

Andy Astbury,noise

Here we see the LUMINANCE noise component – colour & colour noise components have been removed for clarity.

Next, the COLOUR NOISE bit:

Andy Astbury,noise

The COLOUR NOISE component of the area we’re looking at. All luminance noise has been removed.

I must stress that the majority of colour noise you see in your files inside LR,ACR,CapOne,PS etc: is ‘demosaicing colour noise’, which occurs during the demosaic processes.

But the truth is, it’s not that simple.

Localised random colour errors are generated ‘on sensor’ due to the individual sensor characteristics as we’ll see in a moment, because noise, in truth, comes in various guises that collectively effect luminosity and colour:

Andy Astbury,noise

Shot Noise

This first type of noise is Shot Noise – called so because it’s basically an intrinsic part of the exposure, and is caused by photon flux in the light reflected by the subject/scene.

Remember – we see light in a different way to that of our camera. What we don’t notice is the fact that photon streams rise and fall in intensity – they ‘flux’ – these variations happen far too fast for our eyes to notice, but they do effect the sensor output.

On top of this ‘fluxing’ problem we have something more obvious to consider.

Lighter subjects reflect more light (more photons), darker subjects reflect less light (less photons).

Your exposure is always going to some sort of ‘average’, and so is only going to be ‘accurate’ for certain areas of the scene.

Lighter areas will be leaning towards over exposure; darker areas towards under exposure – your exposure can’t be perfect for all tones contained in the scene.

Tonal areas outside of the ‘average exposure perfection’ – especially the darker ones – may well contain more shot noise.

Shot noise is therefore quite regular in its distribution, but in certain areas it becomes irregular – so its often described as ‘pseudo random’ .

Andy Astbury,noise

Read Noise

Read Noise – now we come to a different category of noise completely.

The image is somewhat exaggerated so that you can see it, but basically this is a ‘zero light’ exposure; take a shot with the lens cap on and this is what happens!

What you can see here is the background sensor noise when you take any shot.

Certain photosites on the sensor are actually generating electrons even in the complete absence of light – seeing as they’re photo-voltaic they shouldn’t be doing this – but they do.

Added to this are AD Converter errors and general ‘system noise’ generated by the camera – so we can regard Read Noise as being like the background hiss, hum and rumble we can hear on a record deck when we turn the Dolby off.

Andy Astbury,noise

Thermal & Pattern Noise

In the same category as Read Noise are two other types of noise – thermal and pattern.

Both again have nothing to do with light falling on the sensor, as this too was shot under a duvet with the lens cap on – a 30 minute exposure at ISO 100 – not beyond stupid when you think of astro photography and star trail shots in particular.

You can see in the example that there are lighter and darker areas especially over towards the right side and top right corner – this is Thermal Noise.

During long exposures the sensor actually heats up, which in turn increases the response of photosites in those areas and causes them to release more electrons.

You can also see distinct vertical and some horizontal banding in the example image – this is pattern noise, yet another sensor noise signature.

Andy Astbury,noise

Under Exposure Noise – pretty much what most photographers think of when they hear the word “noise”.

Read Noise, Pattern Noise, Thermal Noise and to a degree Shot Noise all go together to form a ‘base line noise signature’ for your particular sensor, so when we put them all together and take a shot where we need to tweak the exposure in the shadow areas a little we get an overall Under Exposure Noise characteristic for our camera – which let’s not forget, contains other elements of  both luminance noise and colour noise components derived from the ISO settings we use.

All sensors have a base ISO – this can be thought of as the speed rating which yields the highest Dynamic Range (Dynamic Range falls with increasing ISO values, which is basically under exposure).

At this base ISO the levels of background noise generated by the sensor just being active (Pattern,Read & Thermal) will be at their lowest, and can be thought of as the ‘base noise’ of the sensor.

How visually apparent this base noise level is depends on what is called the Signal to Noise Ratio – the higher the S/N ratio the less you see the noise.

And what is it that gives us a high signal?

MORE Photons – that’s what..!

The more photons each photosite on the sensor can gather during the exposure then the more ‘masked’ will be any internal noise.

And how do we catch more photons?

By using a sensor with BIGGER photosites, a larger pixel pitch – that’s how.  And bigger photosites means LESS MEGAPIXELS – allow me to explain.

Buckets in the Rain A

Here we see a representation of various sized photosites from different sensors.

On the right is the photosite of a Nikon D3s – a massive ‘bucket’ for catching photons in – and 12Mp resolution.

Moving left we have another FX sensor photosite – the D3X at 24Mp, and then the crackpot D800 and it’s mental 36Mp tiny photosite  – can you tell I dislike the D800 yet? 

One the extreme left is the photosite from the 1.5x APS-C D7100 just for comparison.

Now cast your mind back to the start of this post where I said we could tentatively regard photons as particles – well, let’s imagine them as rain drops, and the photosites in the diagram above as different sized buckets.

Let’s put the buckets out in the back yard and let’s make the weather turn to rain:

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Various sizes of photosites catching photon rain.

Here it comes…

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

It’s raining

OK – we’ve had 2 inches of rain in 10 seconds! Make it stop!

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

All buckets have 2 inches of water in them, but which has caught the biggest volume of rain?

Thank God for that..

If we now get back to reality, we can liken the duration of the rain downpour as shutter speed, the rain drops themselves as photons falling on the sensor, and the consistency of water depth in each ‘bucket’ as a correct level of exposure.

Which bucket has the largest volume of water, or which photosite has captured the most photons – in other words which sensor has the highest S/N Ratio?   That’s right – the 12Mp D3s.

To put this into practical terms let’s consider the next diagram:

Andy Astbury,Wildlife in Pixels,sensor resolution,megapixels,pixel pitch,base noise,signal to noise ratio

Increased pixel pitch = Increased Signal to Noise Ratio

The importance of S/N ratio and its relevance to camera sensor noise can be seen clearly in the diagram above – but we are talking about base noise at native or base ISO.

If we now look at increasing the ISO speed we have a potential problem.

As I mentioned before, increasing ISO is basically UNDER EXPOSURE followed by in-camera “push processing” – now I’m showing my age..

Andy Astbury,noise,iso

The effect of increased ISO – in camera “push processing” automatically lift the exposure value to where the camera thinks it is supposed to be.

By under exposing the image we reduce the overall Signal to Noise Ratio, then the camera internals lift all the levels by a process of amplification – and this includes amplifying  the original level of base noise.

So now you know WHY and HOW your images look noisy at higher ISO’s – or so you’d think – again,  it’s not that simple; take the next two image crops for instance:

Andy Astbury, iso,noise,sensor noise

Kingfisher – ISO 3200 Nikon D4 – POOR LIGHT – Click for bigger view

Andy Astbury, iso,noise,sensor noise

Kingfisher – ISO 3200 Nikon D4 – GOOD LIGHT – CLICK for bigger view

If you click on the images (they’ll open up in new browser tabs) you’ll see that the noise from 3200 ISO on the D4 is a lot more apparent on the image taken in poor light than it is on the image taken in full sun.

You’ll also notice that in both cases the noise is less apparent in the high frequency detail (sharp high detail areas) and more apparent in areas of low frequency detail (blurred background).

So here’s “The Andy Approach” to noise and high ISO.

1. It’s not a good idea to use higher ISO settings just to combat poor light – in poor light everything looks like crap, and if it looks crap then the image will look even crappier.When I get in a poor light situation and I’m not faced with a “shot in a million” then I don’t take the shot.

2. There’s a big difference between poor light and low light that looks good – if that’s the case shoot as close to base ISO as you can get away with in terms of shutter speed.

3. I you shoot landscapes then shoot at base ISO at all times and use a tripod and remote release – make full use of your sensors dynamic range.

4. The Important One – don’t get hooked on megapixels and so-called sensor resolution – I’ve made thousands of landscape sales shot on a 12Mp D3 at 100 ISO. If you are compelled to have more megapixels buy a medium format camera which will generate a higher S/N Ratio because the photosites are larger.

5. If you shoot wildlife you’ll find that the necessity for full dynamic range decreases with angle of view/increasing focal length – using a 500mm lens you are looking at a very small section of what your eye can see, and tones contained within that small window will rarely occupy anywhere near the full camera dynamic range.

Under good light this will allow you to use a higher ISO in order to gain that crucial bit of extra shutter speed – remember, wildlife images tend to be at least 30 to 35% high frequency detail – noise will not be as apparent in these areas as it is in the background; hence to ubiquitous saying of  wildlife photographers “Watch your background at all times”.

Well, I think that’s enough to be going on with – but there’s oh so much more!

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Wildlife Photography – Common Kestrel

Wildlife Photography How To – Common Kestrel – “Flaps 30, Gear Down, “

As a specialist in natural history and wildlife photography it’s always difficult to decide what are your favorite images from all the frames you shoot – after all, you are quite “emotionally close” to every single one of them!

Being in it to make money in order to live makes the job a little more difficult for the simple reason that, being a photographer, the images you REALLY like are hardly ever the images the picture buyers like. So in order to make a living you have to devote the majority of your camera time to producing commercially viable images – not gallery images.

But occasionally you’ll come up with a shot that satisfies both sides of the equation – you love it yourself and are really proud of it; and it SELLS WELL!

So I thought I’d post a series of my own images that satisfy both myself and the picture buyers, and I’m going to start with one of my top 5 sellers in the last 18 months – your Uncle Andy’s infamous Kestrel shot.

wildlife photography, common Kestrel, photography technique

Common Kestrel Landing
©Andy Astbury/Wildlife in Pixels

Shot in June of 2012 at Poolbridge Farm in Yorkshire, I approached the entire shoot day with this particular shot in mind – you have to have a goal set even with wildlife photography, otherwise you just end up shooting at random; and you HAVE to be in control of at least something other than the camera!

I’d seen all the usual “kestrel perched” shots that were coming out Poolbridge, but I wanted something a little different – and I got this, which was just what I wanted.

Remember PPPPP – positive planning prevents poor performance!

So here’s how the shot was planned and executed:

This position in the Kestrels flight to the perch is BEHIND the perch – in this case an old wooden farm gate – so it happens BEFORE the bird lands on the perch.

So primary focus has to be BEHIND the perch.

Ok, we’re all good so far, but there are some very important factors to take into consideration.  We want a head-on shot, the bird is flying at about 7 meters per second, and we need to take the shot when the bird is around 1 meter behind the perch.

So here’s our main problem – head on means that the closing distance rate between bird and lens is at its fastest possible, and sadly there isn’t an auto focus system on the planet that will keep up with this small target flying straight down the lens axis and guarantee you the shot.

Therefore, sad to say, but AF is out and manual focus is in!

The bird itself is a mature female so she has a wingspan of about 30 inches.

So the shot calls for the following criteria – set the camera at a distance that will capture a 30 inch wide target about 30 inches behind the perch, with a 500mm f4 lens at about 80% of full frame width.  The lens needs to be manually pre-focused at the required distance and an aperture set that will give sufficient depth of field to give a good degree of sharpness over the nearest parts of the bird – beak to feet.

Simple maths tells me I need to have the bird arriving at “position X” about 40 feet or 12 meters in front of the lens.

So now it’s easy; just get my mate Mike who was with me on the day to stand about a meter behind the gate post with his hands outstretched 30 inches apart, frame up so his hands are both well in frame and about a third of the frame from its top edge.  Then manually focus on his cammo patterned shirt front making sure that both lens and camera body are in MF mode and I’m all set to take the shot from a lens point of view.

Set the camera to maximum frame rate (never a good idea usually on a Nikon as it locks the AF but we are not using AF so it doesn’t matter in this instance), and now I’m all set.

The bird is 100% wild and has a nest full of screaming hungry kids to feed, but she knows that if she’s seen people about then there’s usually a tasty morsel of food on the old gate post. She perches in one of two trees while she’s deciding if its safe to come to the perch, but her approach is only head on if she’s coming in from one of them.

So now its just a case of sitting and waiting until she’s in that particular tree, and then waiting some more until she begins her approach.

Once she’s on her way I pick her up in the viewfinder of the camera when she’s about half way across the field (she’s out of focus and very fuzzy when I begin to follow her), keep her fuzzy shape in frame and she gets sharper as she gets closer, then just as she starts to get some some definition to her in the viewfinder I just press and hold down the shutter to shoot an entire buffer full of frames: remembering to keep the camera moving as it was otherwise the composition will be a bit off!

It’s a technique rather like shot-gun shooting – you need to follow trough while squeezing the trigger, otherwise you miss behind!

Don’t get me wrong, the shot wasn’t “in the can” on the first attempt, and nor was it on the forth! But the fifth time she came I nailed it. After that all I had to do was try and repeat the shot over and over again and try to get it all to come together with some good light – we got there in the end.

All in all the shot has made over 500 sales in the last 12 months or so, in all guises from small website jpegs to full size prints – so buyers like it – and I’m pleased with the shot from both an aesthetic and technical standpoint.

And it’s even been on the TV – 4 times now!

So, the job’s a good ‘un!

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