<title>Adaptive transform coding of images based on removing just noticeable distortion</title>

Abstract

The removal of perceptual redundancy from image signals has been considered as a promising approach to maintain high image quality at low bit rates, and has recently become an important area of research. In this paper, a perceptually tuned discrete cosine transform (DCT) coder of gray-scale images is presented, where a just-noticeable distortion (JND) profile is measured as the perceptual redundancy inherent in an image. The JND profile provides each signal being coded with a visibility threshold of distortion, below which reconstruction errors are rendered imperceptible. By exploiting basic characteristics of human visual perception, the JND profile is derived from analyzing local properties of image signals. According to the sensitivity of human visual perception to spatial frequency, a distortion allocation algorithm is applied to each block for screening out perceptually unimportant coefficients (PUC's) and, simultaneously, determining quantizer stepsizes of perceptually important coefficients (PIC's). Simulation results show that high visual quality can be obtained at low bit rates, and, for a given bit rate, the visual quality of the images compressed by the proposed coder is more acceptable than those compressed by ISO-JPEG coder.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.