Title :
Error-diffused image compression using a binary-to-gray-scale decoder and predictive pruned tree-structured vector quantization
Author :
Ting, Ming Yuan ; Riskin, Eve A.
Author_Institution :
Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
fDate :
11/1/1994 12:00:00 AM
Abstract :
The authors consider data compression of binary error diffused images. The original contribution is using nonlinear filters to decode error-diffused images to compress them in the gray-scale domain; this gives better image quality than directly compressing the binary images. Their method is of low computational complexity and can work with any halftoning algorithm
Keywords :
decoding; filtering theory; image coding; nonlinear filters; prediction theory; trees (mathematics); vector quantisation; binary error diffused images; binary-to-gray-scale decoder; data compression; error diffused image compression; gray-scale domain; halftoning algorithm; image quality; low computational complexity; nonlinear filters; predictive pruned tree-structured VQ; vector quantization; Color; Decoding; Digital images; Displays; Histograms; Humans; Image coding; Image processing; Optical distortion; Quantization;
Journal_Title :
Image Processing, IEEE Transactions on
