Title :
The Application of Sparse Coding Algorithm Based on Kurtosis Criterion in Natural Image Compression
Author :
Shang, Li ; Huai, Wen Jun
Author_Institution :
Dept. of Electron. & Inf. Eng., Suzhou Vocational Univ., Suzhou, China
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.
Keywords :
data compression; discrete cosine transforms; edge detection; feature extraction; image coding; independent component analysis; discrete cosine transfer; independent component analysis; kurtosis criterion; natural image compression; natural image edge feature extraction; punitive function; sparse natural image coding algorithm; transformation coding method; Analytical models; Discrete cosine transforms; Feature extraction; Image coding; Independent component analysis;
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
DOI :
10.1109/CCPR.2009.5344107