Use of Gamma Encoder for Image Processing considering Human Visualization

Abstract

processing is a promptly developing field which finds more and more application in various information and technical systems such as: radar-tracking, communications, televisions, Biomedical image, etc. The RGB color model is standard design of computer graphics system is not ideal for all of its applications. The red, green and blue colors are highly correlated. This makes it difficult to execute the image processing algorithm. Gamma encoding of images is required to compensate for properties of human vision, to maximize the use of the bits or bandwidth relative to how humans perceive light and color. Human vision under common illumination conditions follows an approximate gamma or power function. If images are not gamma encoded, they allocate too many bits or too much bandwidth to highlights that humans cannot differentiate, and too few bits/bandwidth to shadow values that humans are sensitive to and would require more bits/bandwidth to maintain the same visual quality. Image enhancement is another technique to improve the image quality for human visualization but sometimes it does not improve the quality when the images need to be darkened or brighten. Hence, this is not a good idea to brighten images all the time when better human visualization can be obtained while darkening the images. Better human visualization is important for manual image processing which leads to compare the outcome with the semi-automated or automated one. Considering the importance of gamma encoding in image processing we propose a new method of image analysis approach which will improve visual quality for manual processing as well as will lead analyzers to analyze images automatically for comparison and testing purpose. Keywordscolor model, Human Visualization, Gamma Encoder, Image processing, RGB Color model.