• DocumentCode
    739216
  • Title

    Image Analysis: Focus on Texture Similarity

  • Author

    Pappas, Thrasyvoulos N. ; Neuhoff, David L. ; de Ridder, H. ; Zujovic, Jana

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
  • Volume
    101
  • Issue
    9
  • fYear
    2013
  • Firstpage
    2044
  • Lastpage
    2057
  • Abstract
    Texture is an important visual attribute both for human perception and image analysis systems. We review recently proposed texture similarity metrics and applications that critically depend on such metrics, with emphasis on image and video compression and content-based retrieval. Our focus is on natural textures and structural texture similarity metrics (STSIMs). We examine the relation of STSIMs to existing models of texture perception, texture analysis/synthesis, and texture segmentation. We emphasize the importance of signal characteristics and models of human perception, both for algorithm development and testing/validation.
  • Keywords
    content-based retrieval; data compression; image retrieval; image segmentation; image texture; video coding; STSIM; content-based retrieval; human perception; image analysis systems; image compression; signal characteristics; structural texture similarity metrics; texture analysis; texture perception; texture segmentation; texture synthesis; video compression; visual attribute; Image analysis; Image coding; Image color analysis; Image segmentation; Texture analysis; Visualization; Matched-texture coding; structural similarity metrics; structurally lossless compression;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/JPROC.2013.2262912
  • Filename
    6553582