Image analysis: Focus on texture similarity

Thrasyvoulos N. Pappas, David L. Neuhoff, Huib De Ridder, Jana Zujovic

Research output: Contribution to journalReview article

18 Scopus citations

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.

Original languageEnglish (US)
Article number6553582
Pages (from-to)2044-2057
Number of pages14
JournalProceedings of the IEEE
Volume101
Issue number9
DOIs
StatePublished - Jan 1 2013

Keywords

  • Matched-texture coding
  • structural similarity metrics
  • structurally lossless compression

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Pappas, T. N., Neuhoff, D. L., De Ridder, H., & Zujovic, J. (2013). Image analysis: Focus on texture similarity. Proceedings of the IEEE, 101(9), 2044-2057. [6553582]. https://doi.org/10.1109/JPROC.2013.2262912