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Adaptive transform coding of images based on removing just noticeable distortion

机译:基于仅消除明显失真的图像自适应变换编码

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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.!11
机译:摘要:从图像信号中去除感知冗余被认为是在低比特率下保持高图像质量的一种有前途的方法,并且近来已成为重要的研究领域。在本文中,提出了一种灰度图像的感知调谐离散余弦变换(DCT)编码器,其中,将刚注意到的失真(JND)轮廓作为图像固有的感知冗余进行了测量。 JND配置文件为每个编码信号提供了失真的可见性阈值,在该阈值以下,无法感知到重构错误。通过利用人类视觉感知的基本特征,JND配置文件是通过分析图像信号的局部属性而得出的。根据人类视觉对空间频率的敏感性,将失真分配算法应用于每个块,以筛选出感知上不重要的系数(PUC),同时确定感知上重要系数(PIC)的量化步长。仿真结果表明,在低比特率下可以获得较高的视觉质量,并且对于给定的比特率,使用拟议编码器压缩的图像的视觉质量比使用ISO-JPEG编码器压缩的图像的视觉质量更可接受。11

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