COMPARISON OF GENERALIZED GAUSSIAN AND LAPLACIAN MODELING IN DCT IMAGE-CODING

被引：91

作者：

JOSHI, RL

FISCHER, TR

机构：

[1] School of Electrical Engineering and Computer Science, Washington State University, Pullman

来源：

IEEE SIGNAL PROCESSING LETTERS | 1995年 / 2卷 / 05期

关键词：

D O I：

10.1109/97.386283

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Generalized Gaussian and Laplacian source models are compared in discrete cosine transform (DCT) image coding, A difference in peak signal to noise ratio (PSNR) of at most 0.5 dB Is observed for encoding different images. We also compare maximum likelihood estimation of the generalized Gaussian density parameters with a simpler method proposed by Mallat. With block classification based on ac energy, the densities of the DCT coefficients are much closer to Laplacian or even Gaussian.

引用

页码：81 / 82

页数：2

共 8 条

[1] ADAPTIVE CODING OF MONOCHROME AND COLOR IMAGES [J].