Wavelet Based Image Coding Schemes : A Recent Survey <s> The Stack-Run (SR) <s> A low complexity wavelet based image coding algorithm for color image compression is presented. The key renovation of this algorithm is that a small number of symbol set was designed to convert the information from the wavelet transform domain into a compact data structure for each subband. The scheme works first by color space conversion, followed by uniform scalar quantization and data conversion where raster scanning order is performed for individual subband and quantized coefficients are converted into the symbol stream according to the designed symbol representation. Two different context lists in each subband are specified from the symbol stream and alternatively compressed by an adaptive arithmetic coder with high efficiency. Unlike zerotree coding or its variations which utilize the intersubband relationship into its own data representation, our work is a low complexity intrasubband based coding method which only addresses the information within the subband. The only extension is the termination symbols which carry the zero value information towards the end of the subband or across the subbands till the end of the image. Compared with the zerotree refined schemes, this algorithm results in competitive PSNR values and perceptually high quality images at the same compression ratio for color image compression. <s> BIB001 </s> Wavelet Based Image Coding Schemes : A Recent Survey <s> The Stack-Run (SR) <s> We propose a multiresolution algorithm to jointly optimize a source coder and channel coder. The variable-rate source coder combines an optimal bit-allocation strategy and efficient stack-run coding. This compression scheme, concatenated with appropriate rate-compatible punctured convolutional codes, provides a competitive approach to state-of-the-art extensions of zerotree methods to noisy channels. Results show that under the assumption of almost zero probability of decoding error, the proposed scheme provides good performance for a lower complexity. <s> BIB002
SR BIB001 image coding algorithm works by the technique of raster scanning BIB002 within subbands. Therefore it involves much lower addressing complexity than other compression algorithms such as zero tree coding which requires creation and maintenance of lists of dependencies across different decomposition levels. The SR algorithm is a new approach in which a 4-ary arithmetic coder is used to represent significant coefficient values and the length of zero runs between coefficients. Despite its simplicity and uncomplicatedness and also the fact that these dependencies are not explicitly used, this algorithm is competitive with the finest enhancements of embedded zero tree wavelet coding.