Mine image enhancement using adaptive bilateral gamma adjustment and double plateaus histogram equalization

Due to the lack of underground space and lighting in coal mine, there are some problems in the mine image, such as poor contrast, uneven illumination, blurred edge and so on. A mine image enhancement method based on cuckoo search is proposed in this paper. This method is based on HSV color space, and uses the Cuckoo Search (CS) algorithm combined with the proposed new conversion function, which utilizes the benefits of both bilateral gamma adjustment (BIGA) function and double plateaus histogram equalization (DPHE). The average brightness is integrated into the evaluation function, and entropy, brightness difference and gray standard variance are used as the objective function of each bird nest to evaluate the mine image enhancement results. The contrast and brightness of image are globally enhanced by finding the optimal parameter values, and the detail enhancement of mine image is achieved. The experimental results show that compared with other traditional and latest image enhancement algorithms, the proposed method can significantly improve the brightness and contrast of mine images, and the image details are richer, and the visual effect is greatly improved.