Abstract
Compressed sensing changes the conventional image processing model of full collection-sampling-compression-transmission-reconstruction and provides a more feasible way to the UAV wireless transmission. Existing matching pursuit algorithms cannot simultaneously meet the requirements of reconstruction accuracy and reconstruction efficiency in UAV wireless transmission, especially when the images are polluted by some noise. Hence, we propose an effective noisy image reconstruction algorithm based on low-rank which introduces the low-rank matrix decomposition and the Augmented Lagrange Multiplier to realize the tradeoff between reconstruction accuracy and reconstruction efficiency. Experimental results verify that the proposed LR algorithm has a superior and stable reconstruction performance on noisy image reconstruction compared with the matching pursuit algorithms.
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