• DocumentCode
    3201202
  • Title

    A New Image Compression Method Based on Primal Sketch Model

  • Author

    Li, Zheng ; Gao, Ruxin ; Guo, Chengen ; Dong, Junyu

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Hubei
  • fYear
    2007
  • fDate
    2-5 July 2007
  • Firstpage
    1451
  • Lastpage
    1454
  • Abstract
    In this paper, we introduce the primal sketch model which might lead to a new image compression method. The primal sketch model integrates two modeling schemes for two type components in natural images: the sketchable and the non-sketchable parts. The sketchable part explains the structural components of the image by using a hidden layer of image primitives. The non-sketchable part denotes the remaining textural components without distinguishable elements by Markov random field models for texture images. The primitives in the image representation are not independent but organized as a sketch graph. The whole image can be coded by a sketch graph with a primitive dictionary and texture descriptors. Such a lossy coding scheme could achieve the compression ratio of 20 to 40 for natural images. With the similar visual effect, the coding length of JFEG2000 is about 1.5 to 3 times higher. This promising compression method could be applied to some situations such as wireless transmission where the bandwidth is critical and low quality images are still acceptable.
  • Keywords
    Markov processes; data compression; image coding; image representation; image texture; JFEG2000; Markov random field models; image compression; image primitives; image quality; image representation; image texture; primal sketch model; primitive dictionary; sketch graph; texture descriptors; Bandwidth; Dictionaries; Image coding; Image representation; Image segmentation; Image storage; Markov random fields; Mathematical model; Pixel; Psychology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2007 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-1016-9
  • Electronic_ISBN
    1-4244-1017-7
  • Type

    conf

  • DOI
    10.1109/ICME.2007.4284934
  • Filename
    4284934