From Event: SPIE Commercial + Scientific Sensing and Imaging, 2018
There are many applications that have corrupted or missing pixels in images. Here, we present sparsity based image completion algorithms that can achieve high performance in image reconstruction. Through extensive experiments using various types of images, it was demonstrated that our algorithms can deal with extremely high missing rates (up to 99.9%) and relatively large missing blocks.
Jin Zhou and Chiman Kwan, "High performance image completion using sparsity based algorithms," Proc. SPIE 10669, Computational Imaging III, 106690I (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 16, 2018; Published: 14 May 2018); https://doi.org/10.1117/12.2303661.
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