Adaptive Dark Channel Prior Enhancement Algorithm for Different Source Night Vision Halation Images

Abstract

The existing enhancement algorithms amplify the halation area and noise when enhancing the night vision halation image. Therefore, this paper proposes an adaptive dark channel prior (ADCP) enhancement algorithm for the different source night vision halation image. The algorithm constructs an adaptive transmittance function according to the relationship between the initial transmittance and the critical gray value of halation. The function can automatically adjust the transmittance according to the halation degree in the night vision image, which ensure the ADCP algorithm to achieve the adaptive enhancement of the images. The experimental results show that the proposed algorithm can effectively improve the clarity and contrast of visible and infrared images in night vision, and avoid over-enhancement of the halation region of visible images. When the proposed algorithm is applied to the anti-halation processing of different source night vision image fusion, the halation elimination of the fused image is more complete, the details of the dark area such as edge, brightness and color are moderately improved, and the overall visual effect is better than the existing enhancement algorithms. The effectiveness and universality of the proposed algorithm are verified for processing different night vision halation scene images.