Multiresolution segmentation-based image coding with hierarchical data structures

This paper presents two multiresolution segmentation-based algorithms for low bit rate image compression using hierarchical data structures. The segmentation is achieved with quadtree and binary space partitioning tree hierarchical data structures and the encoding is performed by using the projection pursuit (matching pursuit) with a finite dictionary of spline functions with various degrees of smoothness. Comparison with JPEG at rates below 0.5 bit/pixel shows superior performance both in terms of peak signal-to-noise ratio (PSNR) and subjective image quality.