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.
- Matched-texture coding
- structural similarity metrics
- structurally lossless compression
ASJC Scopus subject areas
- Electrical and Electronic Engineering