DMCA
doi:10.1155/2009/649316 Research Article A Patch-Based Structural Masking Model with an Application to Compression
BibTeX
@MISC{Ch_doi:10.1155/2009/649316research,
author = {Damon M. Ch and Matthew D. Gaubatz and Sheila S. Hemami},
title = {doi:10.1155/2009/649316 Research Article A Patch-Based Structural Masking Model with an Application to Compression},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
The ability of an image region to hide or mask a given target signal continues to play a key role in the design of numerous image processing and vision systems. However, current state-of-the-art models of visual masking have been optimized for artificial targets placed upon unnatural backgrounds. In this paper, we (1) measure the ability of natural-image patches in masking distortion; (2) analyze the performance of a widely accepted standard masking model in predicting these data; and (3) report optimal model parameters for different patch types (textures, structures, and edges). Our results reveal that the standard model of masking does not generalize across image type; rather, a proper model should be coupled with a classification scheme which can adapt the model parameters based on the type of content contained in local image patches. The utility of this adaptive approach is demonstrated via a spatially adaptive compression algorithm which employs patch-based classification. Despite the addition of extra side information and the high degree of spatial adaptivity, this approach yields an efficient wavelet compression strategy that can be combined with very accurate rate-control procedures. Copyright © 2009 Damon M. Chandler et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
Keyphrases
accurate rate-control procedure original work unnatural background visual masking classification scheme target signal image region creative common attribution license high degree spatial adaptivity patch-based classification key role natural-image patch numerous image processing standard model extra side information report optimal model parameter model parameter vision system adaptive compression algorithm unrestricted use efficient wavelet compression strategy proper model adaptive approach current state-of-the-art model different patch type open access article local image patch artificial target image type
