Irregular image sub-sampling and reconstruction by adaptive sampling

An irregular adaptive sampling algorithm for a compact image representation is presented. A scattered data interpolation algorithm based on an inverse distance weighted method has been chosen. The goal is to compute the values and the locations of a fixed number of samples to approximate efficiently a natural grey-level image. These values are found by the means of a relaxation process. In the context of image coding, the sample values and sample locations have to be coded. A quantization is applied on the sample values and thus reduces the amount of information. The samples location are represented through a binary image which is coded using an arithmetic coder