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A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy

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Abstract

Sand-dust weather seriously reduces the effectiveness of computer vision equipment acquisition. To solve this problem, a fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and an interframe detection strategy is proposed in this paper. First, an adaptive gamma correction with weighting distribution and color balance (AGCWDCB) and adaptive dynamic guided filtering (ADGIF) are used to perform color correction, contrast enhancement and detailed information enhancement on the first frame of the video. Second, the interframe detection model is constructed based on the normalized mean square error information between video frames. Finally, each frame after the first frame of the sand-dust video is processed according to the interframe detection strategy until a sand-dust video with improved quality is obtained. Through qualitative and quantitative comprehensive experiments on sand-dust images and videos, the experimental results are compared with the existing methods, the results of processing sand-dust images using our improved frame method have the best visual effect and the highest total scores in quantitative analysis. The results of interframe detection strategy show average 2.65 × speed up as compared with the frame-wise quality improvement method.

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Funding

This work was supported by the National Science Foundation of China under Grant U1803261 and the International Science and Technology Cooperation Project of the Ministry of Education of the People’s Republic of China under grant 2016-2196.

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Correspondence to Zhenhong Jia.

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Ni, D., Jia, Z., Yang, J. et al. A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy. J Real-Time Image Proc 19, 1181–1197 (2022). https://doi.org/10.1007/s11554-022-01248-6

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