改进的分形矢量量化编码

为了提高图象的分形矢量量化编码效果，在利用四叉树对图象进行自适应分割的基础上，基于正交基三维分量投影准则，提出了图象块非平面近似方法，进而形成一种新的静态图象分形矢量量化编码方法。该方法首先通过对投影参数进行DPCM编码来构造粗糙图象，然后由此来构成差值图象编码的码书。由于该方法把分形和矢量量化编码结合起来，因此解码时只需查找码书，并仅进行对比度变换。计算机编、解码实验结果表明，该编码方法具有码书不需外部训练，解码也不需迭代等优点，且与其他同类编码器相比，该方法在压缩比和恢复图象质量（PSRN）方面均有明显改善。

Modified Fractal Vector Quantization for Image Coding

To improve encoding effectively of fractal vector quantization of image, after using quad tree to segmentation image adaptive, a non plane approximate method of image blocks Based on 3 D projection rule in orthogonal base is proposed in this paper. Furthermore, a novel algorithm for fractal vector quantization of still images is formed. The coarse image is constructed by the DPCM coding method of the projection parameters and the codebook of D value image coding is formed, and we use multiple resolution codebook when D value image coding. This method connects fractal and vector quantization coding together, during the process of decoding, the only need to check the codebook and to transform the contrast. It solves the shortcomings such as slow speed and lower compression ratio existed in traditional methods of fractal image compression well. The result of Computer simulation test of encoding and decoding show that the method does not need training to obtain the codebook in encoding, and not need iteration in decoding, so the method improves compression ratio and reconstructed image quality( PSNR ) obviously.