Image Compression: A Survey <s> Convergent algorithms for succewith applications to wavelet image compression: <s> Embedded wavelet coders have become very popular in image compression applications, owing to their simplicity and high coding efficiency. Most of them incorporate some form of successive approximation scalar quantisation. Recently developed algorithms for successive approximation vector quantisation have been shown to be capable of outperforming successive approximation scalar quantisation ones. In the paper, some algorithms for successive approximation vector quantisation are analysed. Results that were previously known only on an experimental basis are derived analytically. An improved algorithm is also developed and is proved to be convergent. These algorithms are applied to the coding of wavelet coefficients of images. Experimental results show that the improved algorithm is more stable in a rate/spl times/distortion sense, while maintaining coding performances compatible with the state-of-the-art. <s> BIB001 </s> Image Compression: A Survey <s> Convergent algorithms for succewith applications to wavelet image compression: <s> The global maximum of an entropy function with different decision levels for a three-level scalar quantizer performed after a discrete wavelet transform was derived. Herein, we considered the case of entropy-constrained scalar quantization capable of avoiding many compression ratio reductions as the mean squared error was minimized. We also dealt with the problem of minimum entropy with an error bound, which was referred to as the rate distortion function. For generalized Gaussian distributed input signals, the Shannon bound would decrease monotonically when the parameter of distribution /spl gamma/ was to leave from 2. That is Gaussian distributions would contain the highest Shannon bound among the generalized Gaussian distributions. Additionally, we proposed two numerical approaches of the secant and false position methods implemented in real cases to solve the problems of entropy-constrained scalar quantization and minimum entropy with an error bound. The convergence condition of the secant method was also addressed. <s> BIB002
In this study, we will state and prove some properties of the SAVQ algorithm and also propose and analyze a new version of it. This modified algorithm achieve more stable rate x distortion performance in the sense that its parameters can be set PSNR performance regardless of particular image coded also obtained. This is a very desirable result as finding the optimum parameters for each input image would be computationally expensive BIB001 . Global maximum entropy can be observed through three step scalar quantizer performed after discrete wavelet transform. It help us to describe minimum quantization error with entropy constrained and minimum entropy with an error bound, which are useful for applicable in real implementations BIB002 .