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Proceedings Paper

A database of local masking thresholds in natural images
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Paper Abstract

The ability of an image region to hide or mask a target signal continues to play a key role in the design of numerous image-processing and vision applications. However, one of the challenges in designing an effective model of masking for natural images is the lack of ground-truth data. To address this issue, this paper describes a psychophysical study designed to obtain local contrast detection thresholds (masking maps) for a database of natural images. Via a three-alternative forced-choice experiment, we measured the thresholds for detecting 3.7 cycles/deg vertically oriented log-Gabor targets placed within each 85×85-pixel patch (1.9 deg patch) of 15 natural images from the CSIQ image database [Larson and Chandler, JEI, 2010]. Thus, for each image, we obtained a masking map in which each entry in the map denotes the RMS contrast threshold for detecting the log-Gabor target at the corresponding spatial location in the image. Here, we describe the psychophysical procedures used to collect the thresholds, we provide analyses of the results, and we provide some outcomes of predicting the thresholds via basic low-level features, a computational masking model, and two modern imagequality assessment algorithms.

Paper Details

Date Published: 14 March 2013
PDF: 15 pages
Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86510G (14 March 2013); doi: 10.1117/12.2008581
Show Author Affiliations
Md Mushfiqul Alam, Oklahoma State Univ. (United States)
Kedarnath P. Vilankar, Oklahoma State Univ. (United States)
Damon M. Chandler, Oklahoma State Univ. (United States)

Published in SPIE Proceedings Vol. 8651:
Human Vision and Electronic Imaging XVIII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder, Editor(s)

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