Non-uniform correction of infrared image based on adaptive forgetting factor recursive least square method

Chenlong Guo; Xining Liang; Yixuan Liu

doi:10.1117/12.2548113

27 November 2019 Non-uniform correction of infrared image based on adaptive forgetting factor recursive least square method

Chenlong Guo, Xining Liang, Yixuan Liu

Author Affiliations +

Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 1132117 (2019) https://doi.org/10.1117/12.2548113
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China

Abstract

The traditional neural network method is faced with the problem of gradient step size selection when dealing with nonuniform correction of infrared images. When the gradient step size is large, it is easy to cause gradient divergence, and when the gradient step size is small, it is difficult to obtain convergence.At the same time, the algorithm is also prone to ghosting or image blurring. Aiming at this problem, this paper proposes an infrared image non-uniform correction method based on adaptive forgetting factor recursive least squares method. Firstly, this paper deduces the least squares method into the form of incremental calculation, and introduces it into the calculation of the offset and gain of nonuniform correction, so that it can train the infrared image frame by frame. At the same time, this paper considers the problem that the background of the previous frame is learned to generate ghosts in the process of image from long-term still to sudden change, and the calculation of forgetting factor is introduced. And this paper uses local structural similarity index (SSIM) to calculate the forgetting factor. The experimental results show that the iterative step size of the proposed method can be calculated adaptively, without manual adjustment, and can effect overcome the ghost problem. Compared with the traditional neural network method and time domain high-pass filtering method, the algorithm of this paper is the best.

Citation Download Citation

Chenlong Guo, Xining Liang, and Yixuan Liu "Non-uniform correction of infrared image based on adaptive forgetting factor recursive least square method", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132117 (27 November 2019); https://doi.org/10.1117/12.2548113

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