Adaptive transform image coding based on variable-shape block segmentation with smoothing filter

This paper describes a new transform image coding scheme which transfigures square-blocks into variable-shape-blocks so that their boundaries run parallel with the principal contours in an image in order to diminish the coding noise peculiar to transform coding such as the mosquito noise and blocking-effects. This scheme decreases additional information to encode block shapes by limiting all of them to quadrilaterals. Moreover smoothing filter is introduced for the purpose of reducing approximation errors particularly at block boundaries. After determining and encoding block shapes, this scheme transmits a mean value of each block by DPCM and reproduces the interpolation image at both coder and decoder. Then, the interpolation residual signals are selectively encoded by the mean separated KLT whose orthonormal basis-functions are derived individually for each block from the isotropic model for autocorrelation functions of images. Simulation results indicate that this scheme has superiority over square-block-based coding scheme in both coding efficiency and image quality.