Segmentation based distortion equalizing image coding

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2002
İmre, Evren
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In image coding, measures of distortion based on image statistics may be disappointing, if properties of human visual system are not considered. Common problems are smoothed edges and different reconstruction qualities of different regions in the image. This study aims to achieve image coding with perceptually good reconstruction quality, by seeking solutions to the above problems. Proposed scheme, distortion equalizing coder (DEC), is based on contour- texture approach. Image is segmented, and, contour and texture information for each region is encoded separately. Use of contour information prevents smoothing. Equalization of perceived distortion is achieved by first defining a measure of (perceived) distortion, and then, equalizing reconstruction quality for all regions using this measure. This method can be generalized, so that bits can be allocated to regions according to some priority criteria.The study reveals that, although DEC improves visual quality, the rate of the coded image is too high, so, DEC is unfeasible in general. But, its performance may be improved to a point that it may be useful for some specific applications requiring flexibility.
Segmentation based compression, Visual quality, Perceived distortion equalization, Wavelet based coding, Chain coding, Arithmetic coding, Stepwise optimal hierarchical region merging, Watershed algorithm, Binary partition tree
https://hdl.handle.net/11511/12626
Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats
E. İmre, “Segmentation based distortion equalizing image coding,” Middle East Technical University, 2002.
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