Distributed representation of geometrically correlated images with compressed linear measurements

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Vijayaraghavan Thirumalai, Pascal Frossard

Abstract

This paper addresses the problem of distributed coding of images whose correlation is driven by the motion of objects or the camera positioning. It concentrates on the problem where images are encoded with compressed linear measurements. We propose a geometry-based correlation model that describes the common information in pairs of images. We assume that the constitutive components of natural images can be captured by visual features that undergo local transformations (e.g., translation) in different images. We first identify prominent visual features by computing a sparse approximation of a reference image with a dictionary of geometric basis functions. We then pose a regularized optimization problem in order to estimate the corresponding features in correlated images that are given by quantized linear measurements. The correlation model is thus given by the relative geometric transformations between corresponding features. We then propose an efficient joint decoding algorithm that reconstructs the compressed images such that they are consistent with both the quantized measurements and the correlation model. Experimental results show that the proposed algorithm effectively estimates the correlation between images in multiview ...Continue Reading

References

Mar 4, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Yuri Boykov, Vladimir Kolmogorov
Mar 8, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Rosa M Figueras i VenturaPascal Frossard
Jul 1, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Ivana Tosic, Pascal Frossard
Apr 25, 2009·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Oscar Divorra EscodaMichel Bierlaire

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