Comparison of the efficiencies of image compression algorithms based on separable and nonseparable two-dimensional Haar wavelet bases

Compression algorithms for digital images are described that are based on nonseparable two-dimensional wavelet transforms on nonrectangular supports. The efficiencies of these algorithms are experimentally investigated and compared with those of a compression algorithm based on a separable Haar wavelet basis. Aleksandr Mikhailovich Belov. Born 1980. Graduated from the Samara State Aerospace University. Received candidate’s degree in physics and mathematics in 2007. Currently is a junior scientist at the Institute of Image Processing, Russian Academy of Sciences. Scientific interests: discrete orthogonal transforms, fast algorithms for discrete orthogonal transforms, and the theory of canonical number systems. Author of 20 publications, including 8 papers. Member of the Russian Pattern Recognition and Image Processing Association.