Sparse sampling of spectral components in Segmented Planar Imaging Detector for Electro-Optical Reconnaissance is an essential limiting factor to the imaging resolution. A dictionary learning method is proposed to improve the imaging quality. The images are segmented into patches, and data are extracted directly from small patches and taken as dictionary elements. By training high-and-low resolution image pairs, a coupled dictionary is obtained. The TV/L1 minimization and alternating direction multiplier method are used to restore high-resolution images. In this way, the quality metric RMSE of images is improved from 20.99 to 14.99, and PSNR from 21.69 dB to 24.62 dB.
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