DIGITAL COLOR IMAGE ENHANCEMENT BASED ON LUMINANCE SATURATION.

摘要

This dissertation analyzes the different characteristics of color images compared to monochromatic images, combines these characteristics with monochromatic image enhancement techniques, and proposes useful color image enhancement algorithms. Luminance, hue, and saturation (L-H-S) color space is selected for color image enhancement. Color luminance is shown to play the most important role in achieving good image enhancement. Color saturation also exhibits unique features which contribute to the enhancement of high frequency details and color contrast. The local windowing method, one of the most popular image processing techniques, is rigorously analyzed for the effects of window size or weighting values on the visual appearance of an image, and the subjective enhancement afforded by local image processing techniques is explained in terms of the human vision system response. The digital color image enhancement algorithms proposed are based on the observation that the enhanced luminance image results in a good color image in L-H-S color space when the chromatic components (hue, and saturation) are kept the same. The saturation component usually contains high frequency details that are not present in the luminance component. However, processing only the saturation, while keeping the luminance and the hue unchanged, is not satisfactory because the response of human vision system presents a low pass filter to the chromatic components. To exploit high frequency details of the saturation component, we take the high frequency component of the inverse saturation image, which correlates with the luminance image, and process the luminance image proportionally to this inverse saturation image. These proposed algorithms are simple to implement. The main three application areas in image enhancement: contrast enhancement, sharpness enhancement, and noise smoothing, are discussed separately. The computer processing algorithms are restricted to those which preserve the natural appearance of the scene.