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Rapid mismatching elimination algorithm based on motion smoothing constraints
LI Wei, LI Weixiang, ZHANG Fan, JIE Wei
Journal of Computer Applications    2018, 38 (9): 2678-2682.   DOI: 10.11772/j.issn.1001-9081.2018030621
Abstract685)      PDF (1019KB)(333)       Save
To solve the problem of huge computation cost and low matching accuracy in the course of iterative calculation while using RANdom SAmple Consensus (RANSAC) algorithm for image splicing, a mismatching elimination algorithm was proposed based on motion smoothing constraint terms. Firstly, feature points were extracted with ORB (Oriented FAST and Rotated BRIEF) algorithm, and initial matching of feature points was implemented based on Hamming distance. Secondly, the statistical neighboring support estimators based on motion smoothing constraint terms were used to achieve rough mismatching elimination, and then spatial geometric constraints were applied to refine mismatching elimination. Finally, grouping sorting was used to solve the model parameters, and weighted averaging was used to realize image fusion. The experimental results show that the mismatching elimination rate is improved by 75.6% compared to the algorithm for reducing the total number of sampling points and 24% compared to adaptive threshold algorithm. This method can effectively eliminate mismatching and realize accurate image mosaic.
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Single image dehazing algorithm based on sky segmentation
MAO Xiangyu, LI Weixiang, DING Xuemei
Journal of Computer Applications    2017, 37 (10): 2916-2920.   DOI: 10.11772/j.issn.1001-9081.2017.10.2916
Abstract1027)      PDF (829KB)(770)       Save
To address the problem that dark channel prior algorithm is invalid for sky region and the problem that the color of the restored image became darker, a single image dehazing algorithm based on sky segmentation was presented. Firstly, the segmentation algorithm based on edge detection was used to divide the original image into sky region and non-sky region. Then, based on the dark channel prior method, the estimation method for atmospheric light and transmittance was improved for the dehaze of non-sky region. Finally, the sky region was processed by an optimized contrast enhancement algorithm based on cost function. The experimental results demonstrate that, compared with dark channel prior algorithm, many technical specifications of restored images such as variance, average gradient and entropy are greatly improved. The proposed algorithm can effectively avoid the Halo effect in sky region and restore the true scene color while maintaining high operating efficiency.
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