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Operator decomposition using the wavelet transform: fundamental properties and image restoration applications

机译:操作员分解使用小波变换:基本属性和图像恢复应用程序

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A novel formulation of image processing operations in the wavelet domain is presented which directly associates multiresolution with multichannel image processing. The formation of the multiresolution image is expressed as an operator on the image domain that transforms block-circulant structures into partially-block-circulant structures. The proposed implementation relaxes the stationarity and space-invariance assumptions in the image domain and introduces new operator structures for the implementation of single-channel algorithms which take advantage of the correlation structure in the wavelet domain. Based on this structure, the authors discuss the estimation of the power spectrum in the wavelet domain. Image restoration examples using the linear minimum mean square error filter show significant improvement achieved by the proposed approach over the conventional discrete Fourier transform (DFT) implementation.
机译:介绍了小波域中的图像处理操作的新颖制剂,其直接与多通道图像处理相关联。多分辨率图像的形成表示为图像域上的操作员,其将块循环结构转变为部分块循环结构。所提出的实施方式放宽图像域中的实体性和空间不变性假设,并引入新的操作员结构,以实现利用小波域中的相关结构的单通道算法。基于这种结构,作者讨论了小波域中功率谱的估计。通过线性最小均方误差滤波器的图像恢复示例显示了通过在传统的离散傅里叶变换(DFT)实现上所提出的方法实现的显着改进。

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