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Double regularization approach to iterative blind multispectral image restoration

机译:双重正则化方法用于迭代盲多光谱图像复原

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In this paper, we present a new iterative blind multispectral image restoration algorithm based on double regularization (DR). The motivation for DR when applied to multispectral restoration lies in its effectiveness towards edge preservation in joint blur identification and image restoration. With consideration for both the intra- and inter-channel blurring function in the multiple-input multiple-output (MIMO) systems, an alternating minimization (AM) procedure with conjugate gradient optimization (CGO) scheme is formulated to implement restoration iteratively. The derivation of DR optimization shows that optimal restoration result can be achieved even when the MIMO systems suffer from inter-channel interference. Experimental results show that it is effective in performing blind mutichannel restoration when applied to color images.
机译:在本文中,我们提出了一种新的基于双正则化(DR)的迭代盲多光谱图像恢复算法。 DR应用于多光谱恢复的动机在于其在联合模糊识别和图像恢复中对边缘保留的有效性。考虑到多输入多输出(MIMO)系统中的通道内和通道间模糊功能,制定了带有共轭梯度优化(CGO)方案的交替最小化(AM)程序来迭代实现恢复。 DR优化的推导表明,即使MIMO系统受到信道间干扰,也可以实现最佳的恢复结果。实验结果表明,该方法在应用于彩色图像时可以有效地进行盲多通道恢复。

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