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Today’s web-based automatic image enhancement algorithms decide to apply an   enhancement operation by searching for “similar” images in an online database   of images and then applying the same level of enhancement as the image in the   database. Two key bottlenecks in these systems are the storage cost for   images and the cost of the search. Based on the principles of computational   aesthetics, we consider storing task-relevant aesthetic summaries, a set of   features which are sufficient to predict the level at which an image   enhancement operation should be performed, instead of the entire image. The   empirical question, then, is to ensure that the reduced representation indeed   maintains enough information so that the resulting operation is perceived to   be aesthetically pleasing to humans. We focus on the contrast adjustment   operation, an important image enhancement primitive. We empirically study the   efficacy of storing a pixelated summary of the 16 most representative colors   of an image and performing contrast adjustments on this representation. We   tested two variants of the pixelated image: a “mid-level pixelized version”   that retained spatial relationships and allowed for region segmentation and   grouping as in the original image and a “low-level pixelized-random version”   which only retained the colors by randomly shuffling the 50 x 50 pixels. In   an empirical study on 25 human subjects, we demonstrate that the preferred   contrast for the low-level pixelized-random image is comparable to the   original image even though it retains very few bits and no semantic   information, thereby making it ideal for image matching and retrieval for   automated contrast editing. In addition, we use an eye tracking study to show   that users focus only on a small central portion of the low-level image, thus   improving the performance of image search over commonly used computer vision   algorithms to determine interesting key points

Low-level pixelated representations suffice for aesthetically pleasing contrast adjustment in photographs