Dimensional vector and variable resolution quantisation

Abstract

The invention relates to compression coding and / or decoding of digital signals, in particular by vector variable-rate quantisation defining a variable resolution. For this purpose an impulsion dictionary comprises: for a given dimension, increasing resolution dictionaries imbricated into each other and, for a given dimension, a union of: a totality (d'i<N>) of code-vectors produced, by inserting elements taken in a final set (a) into smaller dimension code-vectors according to a final set of predetermined insertion rules (f1) and a second totality of code-vectors (y') which are not obtainable by insertion into the smaller dimension code vectors according to said set of the insertion rules.

Description

Technical field

[0001] The present invention relates to the compression coding and / or decoding of digital signals, including audio, video signals, and more generally multimedia signals used for their storage and / or transmission. Background technique

[0002] Vector quantization is a widely used compression method for digital signals. The primary driving force for using vector quantization is to follow the block coding theory exhibited by Shannon Dingqiang. According to this theorem, increasing the dimensionality of the vector to be coded can achieve better results. Vector quantization uses a vector from a finite set of dimensions to represent an input vector. In this way, the M order (or code vector) is provided to the digitizer to generate a set of input vectors (usually these vectors are an n-dimensional Euclidean real field R n , Or it can be R n A subset of) to R n A non-bijective mapping of a finite subset of Y. This subset Y contains M independent elements:

[0003] Y={y 1 ...

Images