Adaptive rate-distortion-base thresholding: Application in JPEG compression of mixed images for printing

In this paper, we propose a new technique for transform coding based on rate-distortion (RD) optimized thresholding (i.e. discarding) of wasteful coefficients. The novelty in this proposed algorithm is that the distortion measure is made adaptive. We apply the method to the compression of mixed documents (containing text, natural images, and graphics) using JPEG for printing. Although human visual system's response to compression artifacts varies depending on the region, JPEG applies the same coding algorithm throughout the mixed document. This paper takes advantage of perceptual classification to improve the performance of the standard JPEG implementation via adaptive thresholding, while being compatible with the baseline standard. A computationally efficient classification algorithm is presented, and the improved performance of the classified JPEG coder is verified. Tests demonstrate the method's efficiency compared to regular JPEG and to JPEG using non-adaptive thresholding. The non-stationary nature of distortion perception is true for most signal classes and the same concept can be used elsewhere.