A Tree Structured Bayesian Scalar Quantizer for Wavelet Based Image Compression

ABSTRACT the pyramid. Recently, a number of promising quanMultiresolution imagedecompositions (e. g., wavelets), in conjunction with a variety of quantization schemes, have been shown to be very effective for image compression. Recently, several promising tree-structured quantization schemes that exploit the correlation across scales have been proposed. In this paper, we present an image compression algorithm based on a multiresolution Markov random field model used to model the correlations of wavelet coefficients across the scales. We also present experimental results obtained using the algorithm.

• Type: Conference
• Year: 1994
• Where: ICIP
• Authors: Birsen Yazici, Mary L. Comer, Rangasami L. Kashyap, Edward J. Delp
• Keywords: ICIP 1994, Image Compression Algorithm, Image Processing, Promising Tree-structured Quantization, Quantization Schemes