Abstract
AbstractInterpolative DPCM has superior prediction capabilities compared to the commonly used extrapolative DPCM, but since quantization errors accumulate during decoding, and since quantization errors are expanded by expansive coefficients that are proportional to the image size, IDPCM has the weakness that coding errors become excessive. In this paper, offsets are added to the pixel values of the image that is to be coded, where a new method is proposed for the offset adjustments such that a transformed image with smaller quantization errors results. The effectiveness of this algorithm is confirmed by simulations with real images. Since the offset values are determined by the solution of a nonlinear minimization problem with an evaluation function that is the coding error derived from the function of the offsets values and quantization errors of the adjusted image, a minimization algorithm that combines a descent method with a one‐dimensional search and which exploits properties of the evaluation function is used. Furthermore, coded data rates are estimated, and rate‐distortion curves are determined with the use of a hypothesized image probability model. By combining this method with a previously proposed subsampling method, it is possible to improve the image quality by 3 [dB], or reduce the coded rate by 0.3 [bits/pixel].
Published Version
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