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IEEE Transactions on Pattern Analysis and Machine Intelligence
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ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Hybrid 3D fractal coding with neighbourhood vector quantisation
EURASIP Journal on Applied Signal Processing
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Content adaptive mesh representation of images using binary space partitions
IEEE Transactions on Image Processing
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ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Genetic algorithm with a hybrid select mechanism for fractal image compression
Digital Signal Processing
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ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
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Presents a new scheme for fractal image compression based on adaptive Delaunay triangulation. Such a partition is computed on an initial set of points obtained with a split and merge algorithm in a grey level dependent way. The triangulation is thus fully flexible and returns a limited number of blocks allowing good compression ratios. Moreover, a second original approach is the integration of a classification step based on a modified version of the Lloyd algorithm (vector quantization) in order to reduce the encoding complexity. The vector quantization algorithm is implemented on pixel histograms directly generated from the triangulation. The aim is to reduce the number of comparisons between the two sets of blocks involved in fractal image compression by keeping only the best representative triangles in the domain blocks set. Quality coding results are achieved at rates between 0.25-0.5 b/pixel depending on the nature of the original image and on the number of triangles retained