Tuesday 13 October 2015

Colour - Resolution and Colour Sampling

Among the various aspects of this blog the subject of colour has been one of the more interesting and revealing.  Colour in birds is discussed in detail HERE.  From a distance colour plumage patterns may appear quite uniform and homogeneous.  But, take a closer look at say a Northern Wheatear (Oenanthe oenanthe) in the hand or through a scope and one can see that the micro structure of the feather plays an important role in how colours are actually presented to us.

Colour In Layers
The splayed barbs of downier scapular, mantle and coverts feathers add a degree of texture and complexity to a bird's plumage.  By contrast the more tightly-knit barbs of the flight feathers appear less textured, smoother and, as a result may appear more uniformly coloured.  Bird illustrators might resort to crosshatch or fine brush strokes to try and capture this subtle difference in texture.

Take a close look once more for instance at the Northern Wheatear image above.  The highly magnified scapular feathers (lower left inset) have splayed barbs, which in turn reveals a darker background beneath these feathers.  Similarly, on the throat we can see fine white feather barbs, like fine brush strokes lit against a rich, orangish background.  When we pull back and look at the bird in lower resolution (top left) we generally miss these subtle distinctions.  The scapulars appear instead as light tawny with perhaps a hint of fine texture evident.  But the dark background is not so readily apparent.  The throat appears a rather uniform pale orange, though without the same contrast between layers needed to appreciate the texture between the layers of feathers in that area.  Contrast is an important element of all of this.  Contrast determines how the human eye resolves detail and is an essential element of what we term sharpness or acutance, as for instance explored HERE.

For those with experience of handling and describing birds from museum skins or from ringing birds this is perhaps not much of a revelation.  Those who often work up close with birds experience their colours and morphology quite differently to those who watch them solely in the field.  I imagine many field birders miss this subtle distinction between overlapping feather layers and their colours when describing the birds they observe.  I know I have.  Very often when we describe the colours of plumage in the field we are not actually describing the individual feathers.  Very often it is a combination of colours of one or more overlapping feather layers.  This should be borne in mind when it comes to comparing our field descriptions with those obtained from the text of a scientific description, or from a ringer's guide such as the Identification Guide to European Passerines by Lars Svensson or the North American equivalent, the Identification Guide to North American Birds by Peter Pyle for example.

The question is, do we need to be able to observe and capture the kind of detail only obtained by viewing a bird up this close?  Clearly, in most cases we do not.  Standard field guides and their identification plates rarely go into such minute detail and most birds can in fact be described and identified without reference to colour at all.  Moreover, there can be considerable intra-specific variation and variation due to feather moult and wear, particularly involving feather edges and tips.  Not surprisingly then subtle colour detail such as this is not commonly high up the agenda for many birders in the field.

Pixel Resolution
Resolution in photographic terms is the image quality parameter that best represents that distinction between that forensic 'up close and personal' plumage analysis and that, generally far less exacting analysis achievable in the field.  Without a very high level of resolution we can never hope to get down to the fine feather detail needed to for example distinguish between the colours of layers of overlapping feathers as described above.  It is quite rare that a bird will allow such a close approach as this Northern Wheatear.  Typically speaking the image resolution obtainable with a camera in the field is not a close match for such in-the-hand analysis.  In actual fact, most of the time the camera struggles to even come close to capturing the level of detail we can see with our field optics.  Though of course an image may be subject to far more rigorous scrutiny than a field observation, no matter how close and prolonged the sighting.  It could also be said that modern digiscoping and the latest crop of DSLR cameras are making significant ground all the time on field optics in terms of image sharpness, resolution and magnification.  And this trend is only set to continue.

While the resolution we can perceive is dependent on our eye-sight and the resolution of the screen upon which we view our images, we can of course use the zoom function in our imaging software to magnify an image to resolve fine details down to the level of individual pixels.  So when we talk about forensic analysis of detail in digital imagery what really matters is resolution in terms of total pixel count.

The image captured by photographing a bird with a small lens at close range is not the same as the image captured from further away with a longer lens.  Where we are concerned with very fine detail every pixel counts, and that means that image artefacts come into play.

Up closer we can fill the frame and capture the image at much higher resolution.  We also tend to have much better control over lighting and exposure with a smaller lens.  At greater distance we have environmental factors like heat haze, dust and moisture to distort the image.  We rely on larger lenses which generally means compromising optimal exposure and introducing noise and other artefacts.  While these are all clearly important considerations, for this posting I am keeping things rather more simple.  Rather than try and capture similar images of our subject from varying ranges I have instead mimicked this approach by simply taking a really sharp image and gradually lowered its resolution by resizing it smaller.  

There are some similarities between this approach and photographing the subject at varying distances.  The key distinction however is that resizing requires image interpolation which alters every single pixel in the image.  Therefore a resize is an adulteration of the original image content.  On the other hand, when we simply stand further back from our subject and take a smaller image of it we are achieving the same reduction in overall pixel resolution but without that added interpolation step.  Despite all of that, starting with a sharp, well exposed image taken at close range and resizing smaller always tends to produce better, far more reliable results.

Resolution and Sample Homogeneity
I have discussed image colour sampling and analysis is detail elsewhere.  We can sample and identify the colour RGB value for an individual pixel using any standard image editing software.  But when it comes to sampling a patch of colour we face a problem.  The pixels across the surface of a colour swatch will tend to vary slightly, no matter how perfectly homogeneous the swatch might appear.  One need only zoom in to the pixel level to appreciate the level of variation occurring at that minuscule level.  We may inadvertently sample a pixel of noise and end up with a completely spurious result.  Or, for instance in the case of the very sharp image above we may set out to sample the tawny feather colouration of the mantle and inadvertently sample an underlying feather or the feather shaft instead of the barb.  The purpose of the postarizing method that I developed (HERE) is to reduce the margin for error by creating a homogeneous patch, thus eliminating that background noise within the image.  What I am particularly interested in here is the effect of the postarizing method on a really sharp image versus progressively lower resolution images.  Afterall, by resizing an image smaller the interpolation step is liable to introduce a certain amount of portarization itself, filtering out much of the noise in the process.  But the fear might be that in doing so colour accuracy is compromised.

I have already carried out an experiment involving colour patch homogeneity (HERE) and in doing so I think I found a pretty good quality control tool for selection of appropriate sample swatches using defocus as a tool to test homogeneity.  Here I am testing something slightly different.  This is a test of the image resizing interpolation algorithm to see if that process introduces unwanted drift among the colours of the image.

Once again I have taken the very sharp original image.  I have drawn five sample boxes within the image and collected each of those samples.  I have then resized the image and resampled the same boxes over and over at progressively lower image resolutions.  This leaves me with a total of twenty five samples ready for analysis as displayed above (lower left).  The next step involves postarizing each sample.  Once again for this I have used a simple tool in the MS Office 2010 suite called "Cutout".  Taking each swatch in turn this tool reduces the colour pallet of each swatch down to at most two or three sample colours to choose from.  It is quite easy to select a pixel of the appropriate colour from the limited choice.

The results are striking.  Even with the highest resolution image, with its fine textured detail, the postarizing tool has arrived at the same basic colour sample result as the same swatch taken from a much lower resolution image.  For me this strongly suggests that the interpolation tool which I have used to resize the image (MS Paint) is very good at preserving colours down to a very low resolution.

A closer look at the actual RGB numbers shows that there is actually a slight drift evident, most noticeably towards the lower resolutions.  This is not too surprising given that a resize down to 1% of the original image means that every pixel has to somehow convey the detail contained in 100 pixels at high resolution which it has amalgamated and replaced!

Turning to the Birders Colour Pallet which I created to try and put a standard name to colours in sRGB colour space note I have intentionally allowed for a fair degree of latitude between each named colour.  This is an allowance for a fair degree of colour drift during interpolation and other forms of image manipulation.  The result is that, for the most part the Birders Colour Pallet key delivers the same colour result across the board in this experiment.  Only in the case of the dark mauve swatch has the drift exceeded the boundary and arrived at a neighbouring named colour (dark maroon and dark heather in the case of two of the results).  For me these minor outliers are perfectly acceptable and the results further enforce this blog's colour sampling method as a valid and useful one for birders to adopt.

There is a lot to be said for studying plumage up close and personal.  While most field guides and indeed many field observations might give the impression that birds are clad in fairly uniform colours, the reality is plumage colouration is highly complex and subtle at the micro level.  Then again we can get by in the field without having to study birds in such fine detail.  The same can be said for field photography as a means to capture and analyse colour in birds.  What this experiment has shown is that image resolution is not a significant factor we need to be to worry about.  Whether an image is a full frame, high definition mind-bender, or a much lower resolution, simpler representation, it is still possible to analyse colour consistently using the colour sampling method and Birder's Colour Pallet.

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