
pmid: 15825478
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.
Reproducibility of Results, Numerical Analysis, Computer-Assisted, Signal Processing, Computer-Assisted, Data Compression, Image Enhancement, Sensitivity and Specificity, Pattern Recognition, Automated, Multimedia, Artificial Intelligence, Image Interpretation, Computer-Assisted, Computer Graphics, Algorithms
Reproducibility of Results, Numerical Analysis, Computer-Assisted, Signal Processing, Computer-Assisted, Data Compression, Image Enhancement, Sensitivity and Specificity, Pattern Recognition, Automated, Multimedia, Artificial Intelligence, Image Interpretation, Computer-Assisted, Computer Graphics, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 626 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
