Color harmonization

Abstract

Harmonic colors are sets of colors that are aesthetically pleasing in terms of human visual perception. In this paper, we present a method that enhances the harmony among the colors of a given photograph or of a general image, while remaining faithful, as much as possible, to the original colors. Given a color image, our method finds the best harmonic scheme for the image colors. It then allows a graceful shifting of hue values so as to fit the harmonic scheme while considering spatial coherence among colors of neighboring pixels using an optimization technique. The results demonstrate that our method is capable of automatically enhancing the color "look-and-feel" of an ordinary image. In particular, we show the results of harmonizing the background image to accommodate the colors of a foreground image, or the foreground with respect to the background, in a cut-and-paste setting. Our color harmonization technique proves to be useful in adjusting the colors of an image composed of several parts taken from different sources.

What makes an image memorable?

“…As opposed to other image properties, there are no previous studies that try to quantify individual images in terms of how memorable they are, and there are no computer vision systems that try to predict image memorability. This is contrary to many other photographic properties that have been addressed in the literature such as photo quality [16], saliency [10], attractiveness [15], composition [8,18], color harmony [4], and object importance [22]. Also, there are no databases of photographs calibrated in terms of the degree of memorability for each image.…”

Statistics-Based Interactive Evolutionary Computation for Color Scheme Search

“…In this IGA, four pairs of individuals are selected from all individuals including the two elites. This process considers color compatibility on the basis of hue and tone (brightness and saturation) [8,14,22,23]. Thus, for brightness and saturation, an average value and a coefficient of variation are paired.…”

Joint statistical analysis of images and keywords with applications in semantic image enhancement

“…More recent and sophisticated examples are methods to increase region saliency from Fredembach [6] or to adjust color harmony in an image from Cohen-Or et al [3] or Sauvaget and Boyer [21]. Wang et al [26] and Murray et al [15] present methods to adjust an image's color composition with predefined color themes, such as "nostalgic" or "spicy".…”