Successive Refinement for Hypothesis Testing and Lossless One-Helper Problem

Lossless and near-lossless image compression with successive refinement

We present a technique that provides progressive transmission and near-lossless compression in one single framework. The proposed technique produces a bitstream that results in progressive reconstruction of the image just like what one can obtain with a reversible wavelet codec. In addition, the proposed scheme provides nearlossless reconstruction with respect to a given bound after each layer ...

HYPOTHESIS TESTING FOR AN EXCHANGEABLE NORMAL DISTRIBUTION

Consider an exchangeable normal vector with parameters ????2, and ?. On the basis of a vector observation some tests about these parameters are found and their properties are discussed. A simulation study for these tests and a few nonparametric tests are presented. Some advantages and disadvantages of these tests are discussed and a few applications are given.

Successive refinement of information

269 Abslruct-The successive refinement of information consists of first approximating data using a few hits of information, then iteratively improving the approximation as more and more information is supplied. The goal is to achieve an optimal description at each stage. In general an ongoing description is sought which is rate-distortion optimal whenever it is interrupted. It is shown that a r...

Additive successive refinement

Rate-distortion bounds for scalable coding, and conditions under which they coincide with nonscalable bounds, have been extensively studied. These bounds have been derived for the general tree-structured refinement scheme, where reproduction at each layer is an arbitrarily complex function of all encoding indexes up to that layer. However, inmost practical applications (e.g., speech coding) “ad...

0 One Form of Successive Approximation Method and Choice Problem