Example-based color transformation for image and video

Abstract

Color is very important in setting the mood of images and video sequences. For this reason, color transformation is one of the most important features in photo-editing or video post-production tools because even slight modifications of colors in an image can strongly increase its visual appeal. However, conventional color editing tools require user's manual operation for detailed color manipulation. Such manual operation becomes burden especially when editing video frame sequences. To avoid this problem, we previously suggested a method [Chang et al. 2004] that performs an example-based color stylization of images using perceptual color categories. In this paper, we extend this method to make the algorithm more robust and to stylize the colors of video frame sequences. The main extension is the following 5 points: applicable to images taken under a variety of light conditions; speeding up the color naming step; improving the mapping between source and reference colors when there is a disparity in size of the chromatic categories; separate handling of achromatic categories from chromatic categories; and extending the algorithm along the temporal axis to allow video processing. We present a variety of results, arguing that these images and videos convey a different, but coherent mood.