Segmentation-based image compression

A segmentation-based image coding technique is described. Both uniform and textured region extraction algorithms are used for segmentation. Textured regions are reconstructed using 2-D noncausal Gaussian-Markov random field models. Uniform regions are reconstructed using polynomial expansions. An arithmetic coder is used for coding the boundaries of regions. Reasonable quality images are obtained at compression factors of 85:1.

[1]  A B Watson,et al.  Efficiency of a model human image code. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[2]  Jorma Rissanen,et al.  Compression of Black-White Images with Arithmetic Coding , 1981, IEEE Trans. Commun..

[3]  R. Chellappa Two-Dimensional Discrete Gaussian Markov Random Field Models for Image Processing , 1989 .

[4]  Kannan,et al.  ON IMAGE SEGMENTATION TECHNIQUES , 2022 .