ABSTRACT
This chapter introduces three nonstandard image coding techniques: vector quantization (VQ) fractal coding, fractal coding and model-based coding. The VQ, fractal coding, and model-based coding techniques have not been adopted by any image coding standard. However, due to their unique features these techniques may find some special applications. VQ is an effective technique for performing data compression. Theoretically, VQ is always better than scalar quantization because it fully exploits the correlation between components within the vector. The first step of image VQ is the image formation. The image data is first partitioned into a set of vectors. A large number of vectors from various images are then used to form a training set. The training set is used to generate a codebook, normally using an iterative clustering algorithm. The quantization or coding step involves searching, for each input vector, the closest code word in the codebook. The key step of conventional image VQ is the development of a good codebook.
