Visual Signal Analysis: Focus on Texture Similarity

Thrasyvoulos Pappas

(Northwestern University)

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Date: May 6, 2015


Texture is an important visual attribute both for human perception and image analysis systems. We present structural texture similarity metrics (STSIM) and applications that critically depend on such metrics, with emphasis on image compression and content-based retrieval. The STSIM 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. The focus of our current work at Lawrence Livermore is on texture space characterization for surveillance applications.

Further Information:

Thrasos Pappas received the Ph.D. degree in electrical engineering and computer science from MIT in 1987. From 1987 until 1999, he was a Member of the Technical Staff at Bell Laboratories, Murray Hill, NJ. He joined the EECS Department at Northwestern in 1999. He is currently on sabbatical leave at Lawrence Livermore National Laboratory (January to May 2015). His research interests are in human perception and electronic media, and in particular, image and video quality and compression, image and video analysis, content-based retrieval, model-based halftoning, and tactile and multimodal interfaces. Prof. Pappas is a Fellow of the IEEE and SPIE. He has served as editor-in-chief of the IEEE Transactions on Image Processing (2010-12), and technical program co-chair of ICIP-01 and ICIP-09. Prof. Pappas is currently serving as VP-Publications for the Signal Processing Society of IEEE. Since 1997 he has been co-chair of the SPIE/IS&T Conference on Human Vision and Electronic Imaging.

Created: Thursday, May 7th, 2015