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Abstract
An embedded fractal coding scheme is proposed, in this thesis, for low bit rate transmission of discretwavelet transform coefficients for image data compression. Without lost of generalization using 3-level 2-Dimension discrete wavelet transform (2D-DWT) for image data compression, fractal encoding is used for generation of the fractal parameters of the DWT coefficients of the third level subimages (the coarser scale). In this thesis, the fractal encoding is done in the smallest size subimage of level three in order to achieve low bit rate and the lowest possible processing time This should decrease the encoding fractal processing time. The subimages of the third level and that of the subsequent levels (finer scales) are reconstructed from the transmitted fractal parameters of level three by exploring the high correlations among the DWT coefficients in different levels which is named the embedded fractal coding (EFC). For further improvement, an adaptive technique using vector quantization is used to transmit some DWT coefficients. If the block mean square error of the fractal encoding is greater than a given threshold, the block is transmitted using the vector quantization. This Is called the adaptive embedded fractal coding / vector quantization (AEFC/VQ). Experimental results showed that the proposed scheme can provide, with low processing time, good image quality in terms of peak signal to noise ratio (PSNR) and low bit rate.