BTC image coding using mathematical morphology
Qiuheng Wang, Yrjo A. Neuvo · 2003
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.>