Image enhancement on fractional differential for road traffic and aerial images under bad weather and complicated situations

Abstract

To enhance road traffic images and aerial images in bad weather, a new fractional differential operator is studied, and it is different from the traditional Tiansi operator. In the operator, for any sized kernel, the coefficient at the center position is not a constant, and it is the function of the fractional order and the kernel size; for the other pixels in the kernel, there is no zero coefficient value, and the values of the coefficients are calculated according to the distances from the center position on the basis of fractional differential. In experiments, a number of images are tested, and the results show that the studied operator is suitable for the vague images of the low contrast and rich textures, with less color changes. When compared with other newly proposed algorithms (e.g. Dark channel prior and Multiple scale Retinex, etc.) it performs better in some cases.