Kozhemiakin R. Methods of filtering and compression of multichannel remote sensing images based on variational-stabilizing transformation

The research object - process of filtering and compression of multichannel radar and optical images of remote sensing (RS) based on a variance-stabilizing transformations (VST).The research goal - to develop new and improve existing multichannel filtering and image compression VST-based techniques under the presence of complex noise. Research methods - the theory of probability and mathematical statistics, numerical simulation, nonlinear and adaptive digital filtering, spectral and correlation analysis, data compression. Practical value - effective methods for multichannel filtering and image compression are developed. Novelty - first obtained and justified demands to the required accuracy of the estimates of parameters of complex noise that used to apply in the generalized Anscomb VST for filtering and compression; for the first time developed a special type of local VST to filter multichannel radar images; improved multichannel lossy compression method for hyperspectral RS images based on the generalized Anskomb transformation. Level of integration - industrial.Area of using - RS image processing system .