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Sparse geometric image representations with bandelets

机译:带束带的稀疏几何图像表示

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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.
机译:本文介绍了一种新的基类,称为带状基,它沿着多尺度向量分解图像,这些向量在几何流的方向上被拉长。该几何流指示图像灰度级具有规则变化的方向。基于子带的图像分解是通过快速子带滤波算法实现的。 Bandelet基导致几何规则图像的最佳近似率。对于图像压缩和噪声消除应用,可使用快速算法优化几何流,以使最终的bandelet基产生最小的失真。小波图像压缩和噪声去除算法进行了比较。

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