Open Access Presentation
5 October 2015 Visual Signal Analysis: Focus on Texture Similarity (Presentation Recording)
Author Affiliations +
Abstract
Texture is an important visual attribute both for human perception and image analysis systems. We present new structural texture similarity metrics and applications that critically depend on such metrics, with emphasis on image compression and content-based retrieval. The new metrics account for human visual perception and the stochastic nature of textures. They rely entirely on local image statistics and allow substantial point-by-point deviations between textures that according to human judgment are similar or essentially identical.

We also present new testing procedures for objective texture similarity metrics. We identify three operating domains for evaluating the performance of such similarity metrics: the top of the similarity scale, where a monotonic relationship between metric values and subjective scores is desired; the ability to distinguish between perceptually similar and dissimilar textures; and the ability to retrieve "identical" textures. Each domain has different performance goals and requires different testing procedures. Experimental results demonstrate both the performance of the proposed metrics and the effectiveness of the proposed subjective testing procedures.
Conference Presentation

We also present new testing procedures for objective texture similarity metrics. We identify three operating domains for evaluating the performance of such similarity metrics: the top of the similarity scale, where a monotonic relationship between metric values and subjective scores is desired; the ability to distinguish between perceptually similar and dissimilar textures; and the ability to retrieve “identical” textures. Each domain has different performance goals and requires different testing procedures. Experimental results demonstrate both the performance of the proposed metrics and the effectiveness of the proposed subjective testing procedures.

View presentation video on SPIE’s Digital Library:

http://dx.doi.org/10.1117/12.2193656.4449181291001

© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thrasyvoulos N. Pappas "Visual Signal Analysis: Focus on Texture Similarity (Presentation Recording)", Proc. SPIE 9598, Optics and Photonics for Information Processing IX, 959802 (5 October 2015); https://doi.org/10.1117/12.2193656
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KEYWORDS
Visualization

Visual analytics

Signal analysis

Image analysis

Image compression

Stochastic processes

Data processing

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