The Application of Sparse Coding Algorithm Based on Kurtosis Criterion in Natural Image Compression

The Application of Sparse Coding Algorithm Based on Kurtosis Criterion in Natural Image Compression

This paper mainly discussed the algorithm of sparse coding based on the kurtosis criterion and its application in natural image compression. Sparse coding of natural images is in fact a transformation coding method, and it can efficiently perform extracting natural images' features and compress...

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Published in:2009 Chinese Conference on Pattern Recognition pp. 1 - 5
Main Authors: Li Shang, Wen-jun Huai
Format: Conference Proceeding
Language:Chinese
English
Published: IEEE 01-11-2009
Subjects:
Analytical models
Discrete cosine transforms
Feature extraction
Image coding
Independent component analysis
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Abstract This paper mainly discussed the algorithm of sparse coding based on the kurtosis criterion and its application in natural image compression. Sparse coding of natural images is in fact a transformation coding method, and it can efficiently perform extracting natural images' features and compressing images. Utilizing the kurtosis as the punitive function of sparse coding method's sparsity, it can ensure both the sparsity and independence of feature coefficients of natural images, and extract more efficiently the edge features of images. Compared with the image compression methods of standard independent component analysis (ICA) and discrete cosine transfer (DCT), the simulation results show that our method proposed excels in natural image compression.
AbstractList This paper mainly discussed the algorithm of sparse coding based on the kurtosis criterion and its application in natural image compression. Sparse coding of natural images is in fact a transformation coding method, and it can efficiently perform extracting natural images' features and compressing images. Utilizing the kurtosis as the punitive function of sparse coding method's sparsity, it can ensure both the sparsity and independence of feature coefficients of natural images, and extract more efficiently the edge features of images. Compared with the image compression methods of standard independent component analysis (ICA) and discrete cosine transfer (DCT), the simulation results show that our method proposed excels in natural image compression.
Author Li Shang
Wen-jun Huai
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  organization: Dept. of Electron. & Inf. Eng., Suzhou Vocational Univ., Suzhou, China
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Snippet This paper mainly discussed the algorithm of sparse coding based on the kurtosis criterion and its application in natural image compression. Sparse coding of...
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SubjectTerms Analytical models
Discrete cosine transforms
Feature extraction
Image coding
Independent component analysis
Title The Application of Sparse Coding Algorithm Based on Kurtosis Criterion in Natural Image Compression
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