DCT quantization matrices visually optimized for individual images (1993)
Several image compression standards (JPEG, MPEG, H.261) are based on the Discrete Cosine Transform (DCT). These standards do not specify the actual DCT quantization matrix. Ahumada & Peterson and Peterson, Ahumada & Watson provide mathematical formulae to compute a perceptually lossless quantization matrix. Here I show how to compute a matrix that is optimized for a particular image. The method treats each DCT coefficient as an approximation to the local response of a visual "channel." For a given quantization matrix, the DCT quantization errors are adjusted by contrast sensitivity, light adaptation, and contrast masking, and are pooled nonlinearly over the blocks of the image. This yields an 8x8 "perceptual error matrix." A second nonlinear pooling over the perceptual error matrix yields total perceptual error. With this model we may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over imageindependent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.
DCT, images, individual, matrices, optimized, quantization, visually
Proceedings, Human Vision, Visual Processing, and Digital Display IV, Bellingham, WA, SPIE, pp. 202216
