Super-Resolution Reconstruction of Underground Mine Surveillance Images Based on MAP
Underground mine surveillance can record the situation of coal production site timely and accurately. Because of the poor quality of air, inadequate lighting, lower monitor equipment resolution, surveillance images are blurred. This paper makes full use of the complementary information between surveillance images sequence. And we reconstruct high resolution images by using of maximum a posteriori (MAP) algorithm. Experiment results show that the reconstructed images can reflect the detail of the underground mine surveillance images. Compared with the traditional interpolation results, the reconstructed images avoid jagged effect and overall fuzzy. The PSNR of images are also improved.
Yongping Zhang, Linhua Zhou and Elwin Mao
G. L. Fan et al., "Super-Resolution Reconstruction of Underground Mine Surveillance Images Based on MAP", Applied Mechanics and Materials, Vol. 109, pp. 457-461, 2012