Deriving Sparse Coefficients of Wavelet Pyramid Taking Clues from Hough Transform

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AbstractMany applications like image compression requires sparse representation of image. To represent the image by sparse coefficients of transform is an old age technique. Still research is going on for better sparse representation of an image. A very recent technique is based on learning the basis for getting sparse coefficients. But learned basis are not guaranteed to span l 2 space, which is required for reconstruction. In this paper we are presenting a new technique to choose steerable basis of wavelet pyramid which gives sparse coefficients and better reconstruction. Here selection of steerable basis is based on clues from Hough transform.KeywordsOrientation DirectionBand PassSparse RepresentationHough TransformationSparse CoefficientThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.