Simultaneous image transformation and sparse representation recovery

Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse representation is sensitive to image plane transformations such that existing approaches can not reconstruct the sparse representation of a geometrically transformed image. We introduce a simple technique for obtaining transformation-invariant image sparse representation. It is rooted in two observations: 1) if the aligned model images of an object span a linear subspace, their transformed versions with respect to some group of transformations can still span a linear subspace in a higher dimension; 2) if a target (or test) image, aligned with the model images, lives in the above subspace, its pre-alignment versions would get closer to the subspace after applying estimated transformations with more and more accurate parameters. These observations motivate us to project a potentially unaligned target image to rand...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
• Keywords: Aligned Projection Target, Computer Vision, CVPR 2008, Image Plane Transformations, Image Sparse Representation, Transformation-invariant Image Sparse, Unaligned Target Image