Laser & Optoelectronics Progress, Volume. 58, Issue 16, 1610009(2021)
Nonlinear Grayscale Difference Image Registration Based on Stacked Autoencoder Network
Fig. 1. Structure of the neighborhood sampling
Fig. 2. Flow of the feature matching algorithm
Fig. 3. Structure of the SAE network
Fig. 4. Image leuven of the light difference
Fig. 5. Sea ice image. (a) Bohai Sea image (ALOS); (b) Bohai Sea image (ASAR); (c) image with a resolution of 8 m; (d) image with a resolution of 100 m
Fig. 6. Average matching accuracy rates of different algorithms
Fig. 7. Matching results of our algorithm. (a) 1-2; (b) 1-3; (c) 1-4; (d) 1-5; (e) 1-6
Fig. 8. Mismatch elimination results of different algorithms. (a) RANSAC; (b) PSOSAC; (c) LMR; (d) our algorithm
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Chao Huang, Hao Guo, Yan Gao, Jubai An. Nonlinear Grayscale Difference Image Registration Based on Stacked Autoencoder Network[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1610009
Category: Image Processing
Received: Nov. 12, 2020
Accepted: Dec. 14, 2020
Published Online: Aug. 19, 2021
The Author Email: Guo Hao (guohao0512@dlmu.edu.cn)