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Segment-based coding of color images 被引量:2

Segment-based coding of color images
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摘要 Based on the idea of second generation image coding, a novel scheme for coding still images is pre- sented.At first, an image was partitioned with a pulse-coupled neural network; and then an improved chain code and the 2D discrete cosine transform was adopted to encode the shape and the color of its edges respectively.To code its smooth and texture regions, an improved zero-trees strategy based on the 2nd generation wavelet was chosen.After that, the zero-tree chart was selected to rearrange quantified coefficients.And finally some regulations were given according to psychology of various users.Experiments under noiseless channels demonstrate that the proposed method performs better than those of the current one, such as JPEG, CMP, EZW and JPEG2000. Based on the idea of second generation image coding, a novel scheme for coding still images is pre- sented.At first, an image was partitioned with a pulse-coupled neural network; and then an improved chain code and the 2D discrete cosine transform was adopted to encode the shape and the color of its edges respectively.To code its smooth and texture regions, an improved zero-trees strategy based on the 2nd generation wavelet was chosen.After that, the zero-tree chart was selected to rearrange quantified coefficients.And finally some regulations were given according to psychology of various users.Experiments under noiseless channels demonstrate that the proposed method performs better than those of the current one, such as JPEG, CMP, EZW and JPEG2000.
出处 《Science in China(Series F)》 2009年第6期914-925,共12页 中国科学(F辑英文版)
基金 Supported by the Senior University Technology Innovation Essential Project Cultivation Fund Project (Grant No 706028) the Natural Science Fund of Jiangsu Province (Grant No BK2007103)
关键词 image segmentation color image coding lifting scheme wavelet pulse-coupled neural networks structure coding image segmentation color image coding lifting scheme wavelet pulse-coupled neural networks structure coding
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