For years I wrote scientific papers on various topics in image processing, but what I learnt from that process was that few of the papers written are actually meaningful. For instance, in trying to create new image sharpening algorithms many people forgot the whole point of sharpening. Either a photographer strives for sharpness in an entire image or endeavours to use blur as a means of focusing the attention on something of interest in the image (which is in focus, and therefore sharp). Many sharpening algorithms have been developed with the concept of sharpening the whole image… but this is often a falsehood. Why does the photo need to be sharpened? What is the benefit? A simple sharpening with unsharp masking (which is an unfortunate name for a filter) works quite well in its task. But it was designed at a time when images were small, and filters were generally simple 3×3 constructs. Applying the original filter to a 24MP 4000×6000 pixel image will make little, if any difference. On the other hand, blurring an image does nothing for its aesthetics unless it is selective, in essence trying to mimic bokeh in some manner.

Much of what happens in image processing (aside from machine vision) is aesthetically based. The true results of image processing cannot be provided in a quantitative manner and that puts it at odds with scientific methodology. But who cares? Scientific thought in an academic realm is far too driven by pure science with little in the way of pure inventing. But alas few academics think this way, most take on the academic mantra and are hogtied to doing things in a specified way. I no longer prescribe to this train of thoughts, and I don’t really know if I ever did.

This picture shows motion blur which results from a moving subway car, whilst the rest of the picture remains in focus. The motion blur is a part of the intrinsic appeal of the photograph – yet there is no way of objectively quantifying the aesthetic value – it is something that can only be qualitatively and subjectively evaluated.

Aesthetically motivated Image processing is a perfect fit for photographs because while there are theoretical underpinnings to how lenses are designed, and technical principles of how a camera works, the ultimate result – a photograph, is the culmination of the mechanical ability of the camera and the artistic ability of the photographer. Machine vision, the type used in manufacturing facilities to determine things like product defects is different, because it is tasked with precision automated photography in ideal controlled conditions. To develop algorithms to remove haze from natural scenes, or reduce glare is extremely difficult, and may be best taken when thee is no haze. Aesthetic-based picture processing is subjectively qualitative and there is nothing wrong with that. It is one of the criteria that sets humans apart from machines – the inherent ability to visualize things differently. Some may find bokeh creamy while others may find it too distractive, but that’s okay. You can’t create an algorithm to describe bokeh because it is an aesthetic thing. The same way it’s impossible to quantify taste, or distinguish exactly what umami is.

Consider the following quote from Bernard Berenson (Aesthetics, Ethics, and History) –

‘The eyes without the mind would perceive in solids nothing but spots or pockets of shadow and blisters of light, chequering and criss-crossing a given area. The rest is a matter of mental organization and intellectual construction. What the operator will see in his camera will depend, therefore, on his gifts, and training, and skill, and even more on his general education; ultimately it will depend on his scheme of the universe.’