Abstract
Smoothing filters are widely used in computer vision and computer graphics. Bilateral filtering is a typical edge-preserving filter, which has the advantages of sharpening the image edge contour and denoising. The traditional adaptive bilateral filtering algorithms only considered the spatial variance and the adaptation of gray-scale variance which ignores the influence of the convolution kernel on infrared images. In this paper, an adaptive bilateral filter method improved convolution kernel is proposed for infrared image enhancement which combines the edge detection operator with bilateral filtering. The method primarily combines the advantages of edge detection operators to propose an improved convolution kernel in bilateral filtering. The main purpose of the proposed method is used to enhance the details of infrared images and suppress noise. The effective of the proposed method is verified by the experiment.
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Lv, H., Shan, P., Shi, H. et al. An adaptive bilateral filtering method based on improved convolution kernel used for infrared image enhancement. SIViP 16, 2231–2237 (2022). https://doi.org/10.1007/s11760-022-02188-1
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DOI: https://doi.org/10.1007/s11760-022-02188-1