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Image Compression – Facial Images

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Sparse and Redundant Representations
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Abstract

The sparse-representation viewpoint discussed so far, along with dictionary-learning, is merely that – a viewpoint. The theoretical results we have given merely tell us that sparse modeling is, in favorable cases, a mathematically well-founded enterprize with practically useful computational tools. The only way to tell if sparse modeling works in the real world is to apply it, and see how it performs! We have already seen the use of sparse representation modeling for image deblurring, and the results seem to be promising. In this and the next chapters, we review selected results applying this viewpoint to several image processing tasks.

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Correspondence to Michael Elad .

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Elad, M. (2010). Image Compression – Facial Images. In: Sparse and Redundant Representations. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7011-4_13

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