A binary wavelet transform (BWT) has several distinct advantages over a real wavelet transform when applied to binary data. No quantisation distortion is introduced and the transform is completely invertible. Since all the operations involved are modulo-2 arithmetic, it is extremely fast. The outstanding qualities of the BWT make it suitable for binary image-processing applications. The BWT, originally designed for binary images, is extended to the lossless compression of grey-level images. An in-place implementation structure of the BWT is explored. Then, a simple embedded lossless BWT-based image-coding algorithm called progressive partitioning binary wavelet-tree coder (PPBWC) is proposed. The proposed algorithm is simple in concept and implementation, but achieves promising lossless compression efficiency as compared with the conventional bitplane scanning methods. Small alphabets in the arithmetic coding, non-causal adaptive context modelling and source division are the major factors that contribute to the gain of compression efficiency of the PPBWC. Experimental results show that the PPBWC outperforms most of other embedded coders in terms of coding efficiency.
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering