The discrete curvelet transform decomposes an image into a set of fundamental components that are distinguished by direction and size and a low-frequency representation. The curvelet representation of a natural image is approximately sparse; thus, it is useful for compressed sensing.
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Utilizing the structure of a redundant dictionary comprised of wavelets and curvelets with compressed sensing
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Written by Journal of Electronic Imaging on December 6, 2022
Topics: Press Coverage