Laser & Optoelectronics Progress, Volume. 56, Issue 21, 211005(2019)
Remote Sensing Image S-Type Fusion/Stitching via Low-Error Matching Strategy
To solve the current issues of low effective matching rate and large stitching error of the remote sensing image mosaic algorithm, the matching and fusion/stitching processes of a remote sensing image mosaic algorithm are investigated herein. This algorithm utilizes a guided filter to preprocess the images. Based on the fast and efficient speed-up robust feature approach and the low-error bidirectional mutual selection matching strategy, the matching feature points are further purified by the random sample consensus algorithm; then, a homography transformation matrix is adopted to calculate the relative positional relationship between the images. In the fusion/stitching phase, the image fusion algorithm is modified according to Weber's law and the plant growth function. Finally, image fusion stitching is completed using the nonlinear S-type nonlinear fusion strategy. The simulations reveal improvements in the matching accuracy, average gradient of the image fusion/stitching resultant graph, and information entropy by approximately 1.01%-3.42%, 84.86%-146.26%, and 0.77%-2.22%, respectively. Thus, with respect to realizing high-efficiency and low-error remote sensing image matching, improved splicing quality and efficiency as well as high robustness of the fusion algorithm are achieved.
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Xiaoqian Gao, Fan Yang, Hairui Fan, Hongyu Zhu, Xuejiao Li. Remote Sensing Image S-Type Fusion/Stitching via Low-Error Matching Strategy[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211005
Category: Image Processing
Received: Mar. 4, 2019
Accepted: May. 5, 2019
Published Online: Nov. 2, 2019
The Author Email: Yang Fan (commanderjy@163.com)