In image processing, have we have forgotten about aesthetic appeal?

In the golden days of photography, the quality and aesthetic appeal of the photograph was unknown until after the photograph was processed, and the craft of physically processing it played a role in how it turned out. These images were rarely enhanced because it wasn’t as simple as just manipulating it in Photoshop. Enter the digital era. It is now easier to take photographs, from just about any device, anywhere. The internet would not be what it is today without digital media, and yet we have moved from a time when photography was a true art, to one in which photography is a craft. Why a craft? Just like a woodworker crafts a piece of wood into a piece of furniture, so to do photographers  crafting their photographs in the like of Lightroom,or Photoshop.There is nothing wrong with that, although I feel like too much processing takes away from the artistic side of photography.

Ironically the image processing community has spent years developing filters to process images, to make them look more visually appealing – sharpening filters to improve acuity, contrast enhancement filters to enhance features. The problem is that many of these filters were designed to work in an “automated” manner (and many really don’t work well), and the reality is that people prefer to use interactive filters. A sharpening filter may work best when the user can modify its strength, and judge its aesthetic appeal through qualitative means. The only place “automatic” image enhancement algorithms exist are those in-app filters, and in-camera filters. The problem is that it is far too difficult to judge how a generic filter will affect a photograph, and each photograph is different. Consider the following photograph.

Cherries in a wooden bowl, medieval.

A vacation pic.

The photograph was taken using the macro feature on my 12-40mm Olympus m4/3 lens. The focal area is the top-part of the bottom of the wooden bucket. So some of the cherries are in focus, others are not, and there is a distinct soft blur in the remainder of the picture. This is largely because of the low depth of field associated with close-ip photographs… but in this case I don’t consider this a limitation, and would not necessarily want to suppress it through sharpening, although I might selectively enhance the cherries, either through targeted sharpening or colour enhancement. The blur is intrinsic to the aesthetic appeal of the image.

Most filters that have been incredibly successful are usually proprietary, and so the magic exists in a black box. The filters created by academics have never faired that well. Many times they are targeted to a particular application, poorly tested (on Lena perhaps?), or not at all designed from the perspective of aesthetics. It is much easier to manipulate a photograph in Photoshop because the aesthetics can be tailored to the users needs. We in the image processing community have spent far too many years worrying about quantitative methods of determining the viability of algorithms to improve images, but the reality is that aesthetic appeal is all that really matters. Aesthetic appeal matters, and it is not something that is quantifiable. Generic algorithms to improve the quality of images don’t exist, it’s just not possible in the overall scope of the images available. Filters like Instagram’s Larkwork because they are not changing the content of the image really, they are modifying the colour palette, and they do that applying the same look-up table for all images (derived from some curve transformation).

People doing image processing or computer vision research need to move beyond the processing and get out and take photographs. Partially to learn first hand the problems associated with taking photographs, but also to gain an understanding of the intricacies of aesthetic appeal.

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