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Parallel multiframe blind deconvolution using wavelength diversity

机译:使用波长分集的并行多帧盲解卷积

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The resolution of images captured through ground-based telescopes is generally limited by blurring effects due to atmospheric turbulence. We have developed a method to estimate both the original objects and the blurring function from a sequence of noisy blurred images, simultaneously collected at different wavelengths (wavelength diversity). The assumption of common path-length errors across the diversity channels allows for a parallel deconvolution procedure that exploits this coupling. In contrast with previous work, no a priori assumptions about the object's intensity distribution are required. The method is described, and preliminary results with real images collected with a bench-scale imaging system are presented, demonstrating the promise of the algorithm.
机译:通过地面望远镜捕获的图像的分辨率通常受到大气湍流造成的模糊影响的限制。我们已经开发了一种方法,可以从一系列嘈杂的模糊图像(同时在不同波长(波长分集)处同时收集)中估计原始对象和模糊功能。跨分集信道的公共路径长度误差的假设允许利用该耦合的并行去卷积过程。与以前的工作相反,不需要关于对象的强度分布的先验假设。描述了该方法,并给出了用台式成像系统收集的真实图像的初步结果,证明了该算法的前景。

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