Two error resilient coding schemes for wavelet-based image transmission based on data embedding and genetic algorithms

For an entropy-coded wavelet-based image, such as a JPEG-2000 image, a transmission error in a codeword will not only affect the underlying codeword but may also affect subsequent codewords, resulting in a great degradation of the received image. In this study, two error resilient coding schemes for wavelet-based image transmission based on data embedding and genetic algorithms (GA’s) are proposed.In this study, using JPEG-2000, an image is decomposed into six wavelet levels (levels 0–5). At the encoder, for levels 0–2, some important data useful for error concealment performed at the decoder are extracted and embedded into the compressed JPEG-2000 image bitstream. At the decoder, the important (embedded) data for each corrupted code block are extracted and used to facilitate error concealment. For levels 3–5, the wavelet coefficients of each corrupted code block are simply replaced by zeros.Based on the simulation results obtained in this study, the performances of the two proposed schemes are better than those of three comparison approaches, namely, the Zero-S, Mean-S, and Inter approaches. The proposed schemes can recover high-quality wavelet-based JPEG-2000 images from the corresponding corrupted images up to a bit error rate of 0.5%.