A Patch-Based Structural Masking Model with an Application to Compression. (13th April 2009)

• Record Type: Journal Article
• Authors: Chandler Chandler, Damon M. Damon M.; Gaubatz Gaubatz, Matthew D. Matthew D.; Hemami Hemami, Sheila S. Sheila S.
• Other Names: Lucey Lucey Simon Simon Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2009(2009)
• Publication Date: 2009-04-13
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2009/649316
• Languages: English
• ISSNs: 1687-5176

Abstract

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.