Sparse geometric image representations with bandelets.

Erwan Le Pennec; Stéphane Mallat

doi:10.1109/tip.2005.843753

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Sparse geometric image representations with bandelets.

Erwan Le Pennec·Stéphane Mallat

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Abstract

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.

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Algorithms Artificial Intelligence Computer Graphics Data Compression Image Enhancement Image Interpretation, Computer-Assisted Multimedia Numerical Analysis, Computer-Assisted Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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Erwan Le Pennec, Stéphane Mallat. 2005. Sparse geometric image representations with bandelets.. https://doi.org/10.1109/tip.2005.843753

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