针对低照度图像增强过程中存在的光晕伪影、边缘细节丢失和噪声放大等问题,提出了一种结合双通道先验和光照图引导滤波的图像增强算法。传统去雾物理模型仅基于暗通道先验进行图像增强,局部区域景深不同,进而导致图像过曝和光晕伪影等问题。针对该问题,采取亮暗双通道结合的方法求取大气光值和透射率。对于边缘信息易丢失的问题,采取光照图梯度域引导滤波来改善细化透射率。对于增强过程中噪声放大的问题,采取BM3D滤波进行去噪。实验结果表明,在不同情况下的低照度图像中,该算法相对于其他低照度增强算法,在去噪、光晕消除、亮度调整和边缘保持等方面都有明显的提升。

Aiming at the problems of halo artifacts, edge details loss and noise amplification in the low-illumination image enhancement process, an image enhancement algorithm was proposed based on dual-channel prior and illumination map guided filtering. As the traditional fog-degradation model only uses dark-channel prior for image enhancement, local areas have different depths of field, which thus results in the problems such as image overexposure and halo artifacts. As for these problems, the bright and dark dual-channel integration method is adopted to calculate the atmospheric optical value and transmittance. As for the problem that edge information is easy to be lost, the illumination map gradient domain guided filtering is adopted to improve and refine transmittance. As for the problem of noise amplification in the enhancement process, the BM3D filtering is adopted for denoising. The experimental results indicate that, in different low-illumination images, the proposed algorithm shows an obvious improvement in denoising, halo eliminating, brightness adjustment and edge preservation if compared with other low illumination enhancement algorithms.