Title :
Image compression by variable block truncation coding with optimal threshold
Author :
Kamel, Mohamed ; Sun, C.T. ; Guan, Lian
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
fDate :
1/1/1991 12:00:00 AM
Abstract :
A variable block truncation coding (BTC) algorithm is proposed for image compression. It is shown that there exists an optimal threshold for the quantization in BTC algorithms (fixed and variable) that minimizes the errors. Compared to the fixed BTC (fBTC), the variable BTC (vBTC) gives better performance on all the tested images. The use of vBTC with optimal threshold leads to a reduction of the error in the reconstructed images by almost 40% of the error in the reconstructed images obtained by fBTC. This enhanced performance suggests that the vBTC with optimal threshold is a better alternative to the fixed block truncation coding
Keywords :
data compression; encoding; picture processing; image coding; image compression; optimal threshold; quantization; variable block truncation coding; Image coding; Image reconstruction; Machine intelligence; Mean square error methods; Pattern analysis; Pixel; Sun; System analysis and design; Tail; Vector quantization;
Journal_Title :
Signal Processing, IEEE Transactions on
