| Summary: | Abstract Due to the lack of underground space and lighting in coal mines, coal mine images suffer from low contrast, poor clarity and uneven brightness, which severely obstacles the visual task achievement in underground coal mines. Since the coal mine dust image has a special black shift, the existing ground and underwater defogging methods cannot play a role in the coal mine dust image with the black shift. Therefore, this paper proposes a method of coal mine dust image defogging with a three-stream and three-channel color balance, which is specially used for the restoration of disturbed coal mine images. The method performs color balance on the image R, G, and B channels respectively to eliminate the color shift caused by the coal mine environment; then uses a quad-tree subdivision search algorithm and dark channel prior to obtain the atmospheric light and transmittance of the three-channel color balanced image, respectively; then proposes a weighting algorithm to realize transmittance fusion of three-stream coal mine images, and finally realizes coal mine dust image defogging according to the haze weather degradation model. Extensive experimental results on the ground, underwater, sand and dust images and real coal mine images show that our method outperforms state-of-the-art coal mine dust image defogging algorithms and has good generality.
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