Title :
BTC image coding using mathematical morphology
Author :
Wang, Qiaofei ; Neuvo, Yrjö
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
Abstract :
The application of mathematical morphology to block truncation coding (BTC) image coding is investigated. First the overhead statistical information, namely, sample mean and sample variance, are encoded using the DPCM technique with adaptive morphological predictors. Then the authors propose utilizing the roots of morphological filters to compress the bits for the bit plane. Compared to the standard BTC coding method, the bits/pixel needed are reduced according to the local statistics of an image. The results were comparable to or slightly better than the results obtained by a median-based BTC image coding scheme
Keywords :
block codes; encoding; filtering and prediction theory; image processing; mathematical morphology; pulse-code modulation; BTC; DPCM; adaptive morphological predictors; block truncation coding; differential pulse code modulation; image coding; image processing; mathematical morphology; morphological filters; sample mean; sample variance; Filtering; Filters; Gray-scale; Image coding; Image communication; Laboratories; Morphology; Pixel; Signal processing; Statistics;
Conference_Titel :
Systems Engineering, 1992., IEEE International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-0734-8
DOI :
10.1109/ICSYSE.1992.236906
