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Sparse geometric image representations with bandelets
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DOI：10.1109/TIP.2005.843753.png)
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Abstract
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This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates directions in which the image gray levels have regular variations. The image decomposition in a bandelet basis is implemented with a fast subband-filtering algorithm. Bandelet bases lead to optimal approximation rates for geometrically regular images. For image compression and noise removal applications, the geometric flow is optimized with fast algorithms so that the resulting bandelet basis produces minimum distortion. Comparisons are made with wavelet image compression and noise-removal algorithms.
Keywords:
nonlinear filtering and enhancement (2-NFLT)
still image coding (I-STIL)
wavelets and multiresolution processing (2-WAVP)
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13.7
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