Research on an improved algorithm for image dehazing in underground coal mine

Abstract

Coal mine images have low illuminance, large dust and high noise intensity, etc. It brings great obstacle to extract effective image information. This paper proposes an image haze removal algorithm for coal mine underground based on dark channel prior. First, histogram equalization method is introduced to enhance the underground image, obtain the dark channel image from the thumbnail of the image, and then restore the pixel value of the image through bilinear interpolation, for shortening the acquisition time of the dark channel image and increasing the speed of the algorithm. Results demonstrate this method greatly reduces the amount of calculation and improves the processing speed of the haze removal algorithm while ensuring the haze removal effect.

The application of mammography imaging in the diagnosis and prediction of breast diseases

“…Mammography images can fully reflect the anatomy of the whole breast, presenting most of the features for qualitative diagnosis, and in particular, clearly showing the micro calcified foci of breast lesions. Therefore, most studies adopt molybdenum images, a considerable number of studies utilize ultrasound images, and a minority of studies used MRI [10].…”