• DocumentCode
    2543116
  • 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
  • fYear
    2009
  • fDate
    4-6 Nov. 2009
  • Firstpage
    1
  • Lastpage
    5
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4199-0
  • Type

    conf

  • DOI
    10.1109/CCPR.2009.5344107
  • Filename
    5344107