Báo cáo hóa học: "Research Article A Patch-Based Structural Masking Model with an Application to Compression"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Patch-Based Structural Masking Model with an Application to Compression | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2009 Article ID 649316 22 pages doi 2009 649316 Research Article A Patch-Based Structural Masking Model with an Application to Compression Damon M. Chandler 1 Matthew D. Gaubatz 2 and Sheila S. Hemami3 1 School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA 2Print Production Automation Lab HP Labs Hewlett-Packard Palo Alto CA 94304 USA 3 School of Electrical and Computer Engineering Cornell University Ithaca NY 14853 USA Correspondence should be addressed to Matthew D. Gaubatz Received 26 May 2008 Accepted 25 December 2008 Recommended by Simon Lucey 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 .

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