Adaptive Deconvolution for Pushbroom Hyperspectral Imaging Systems
نویسندگان
چکیده
This paper introduces a framework based on the LMS algorithm for sequential deconvolution of images acquired by a pushbroom hyperspectral imaging system. Considering a sequential model of image blurring phenomenon, we derive a zero-attracting LMS (ZA-LMS) algorithm for 2D image deconvolution. Its transient behavior is analyzed in the mean and mean-square sense. For hyperspectral images, a spectral regularizer is added to promote a coupling between spectral bands. Simulation results are presented to evaluate the accuracy of the transient performance analysis and to illustrate the effectiveness of the deconvolution algorithm.
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تاریخ انتشار 2016