COLOR IMAGE COMPRESSION USING QUANTIZATION, THRESHOLDING, AND EDGE-DETECTION TECHNIQUES ALL BASED ON THE MOMENT-PRESERVING PRINCIPLE

Authors
Citation
Ck. Yang et Wh. Tsai, COLOR IMAGE COMPRESSION USING QUANTIZATION, THRESHOLDING, AND EDGE-DETECTION TECHNIQUES ALL BASED ON THE MOMENT-PRESERVING PRINCIPLE, Pattern recognition letters, 19(2), 1998, pp. 205-216
Citations number
NO
Categorie Soggetti
Computer Science Artificial Intelligence","Computer Science Artificial Intelligence
Journal title
ISSN journal
01678655
Volume
19
Issue
2
Year of publication
1998
Pages
205 - 216
Database
ISI
SICI code
0167-8655(1998)19:2<205:CICUQT>2.0.ZU;2-T
Abstract
A new approach to color image compression with high compression ratios and good quality of reconstructed images using quantization, threshol ding, and edge detection all based on the moment-preserving principle is proposed, An input image with 24 bits per pixel is quantized into 8 bits per pixel using a new color quantization method based on the mom ent-preserving principle. The quantized image is then divided into n x n non-overlapping square blocks. Two representative colors for each b lock are computed by moment-preserving thresholding. A bit-map is then generated, consisting of 0s and 1s indicating whether the block pixel s are assigned to the first color or the second according to the Eucli dean distance measure. A moment-based edge detector is performed furth er on the bitmap of each non-uniform block. The two parameters iota an d theta of a line edge with the equation of x cos theta + gamma sin th eta = iota are obtained. The image is finally coded with a codebook of a 256-color palette; a 1-bit indicator for each block which specifies whether the block is uniform or not; an 8-bit color index for a unifo rm block, or two 8-bit color indices, a 3-bit index for theta, and a 2 -bit or 3-bit index for iota for a non-uniform block. An average compr ession ratio of 22.49 or 33.32 can be obtained for 4 x 4 or 5 x 5 imag e blocks, respectively. Experimental results show the feasibility and efficiency of the proposed approach for color image compression. (C) 1 998 Elsevier Science B.V, All rights reserved.