Professional photographers compose and process an image to emphasise the image's subject. Images with high salience, where a region is highly distinct from its background, are perceived to be of much greater quality in panel tests. Because of technical and expertise considerations, “average” camera users often capture images that have a lesser salience, thereby decreasing the image's appeal.The standard workflow to increase the perceived salience of an image's main subject consists in identifying the region of interest, and processing that region according to a set of rules. The level of analysis and processing can greatly vary, from increasing saturation or sharpness to identifying semantic concepts, e.g., faces, and employ a complex, tailored, modification.This is a delicate problem to approach: saliency prediction algorithms are currently not precise enough, and region classification is necessarily limited to a few specific classes. Furthermore, the variety of content often precludes the usage of a fixed set of rules in the enhancement step.Rather than attempting to predict saliency in images, we propose that important regions are somewhat distinct from their surroundings and can be identified by features that are spatially compact, in addition to standard compositional cues. Having identified the region of interest, we provide an enhanced image by increasing the values of its compact feature(s), i.e., increasing the perceived saliency of the region of interest. Preference studies indicate our modified images are significantly preferred to the original ones.
Clément Fredembach, "Saliency as compact regions for local image enhancement" in Proc. IS&T 19th Color and Imaging Conf., 2011, pp 14 - 18, https://doi.org/10.2352/CIC.2011.19.1.art00004