Context-based bit plane golomb coder for scalable image coding

Abstract

With the increasing use of digital images and delivering those images over networks, scalable image compression systems such as the wavelet based image compression standard JPEG2000 are very attractive.In this thesis, we present the proposed wavelet-based coder, Context-based Bit Plane Golomb Coding (CB-BPGC) for scalable image coding by combining the Bit Plane Golomb Coding (BPGC), a low complexity embedded compression strategy for Laplacian distributed sources, with image context modeling techniques. Compared to JPEG2000, CB-BPGC provides better lossless compression ratio and comparable lossy coding performance by exploring the characteristics of wavelet coefficients. Fortunately, compression performance improvement is achieved together with a lower complexity in CB-BPGC. CB-BPGC is also more resilient to channel errors when simulated on the wireless Rayleigh fading channel compared to JPEG2000. Both the Peak Signal-to-Noise Ratio (PSNR) and the subjective performance of the corrupted images are better.