Restoration of Color-Quantized Images

색상 양자화된 영상의 복원

Color quantization replaces the color of each pixel with the closest representative color, and thus it makes the resulting image partitioned into uniformly-colored regions. As a consequence, continuous, detailed variations of color over the corresponding regions in the original image are lost through color quantization. In this paper, we present a novel scheme for restoring such variations from a color-quantized input image. Our scheme identifies which pairs of uniformly-colored regions in the input image should have continuous variations of color in the resulting image. Then, such regions are seamlessly stitched using the Laplace equation. The user can optionally indicate which regions should be separated or stitched by scribbling constraint brushes across the regions. We demonstrate the effectiveness of our approach through diverse examples, such as photographs, cartoons, and artistic illustrations.