基于同态频分聚合的低照度图像增强算法

Low-Light Image-Enhancement Algorithm Based on Homomorphic Frequency Division Aggregation

弱光环境会导致图像采集设备拍摄的照片出现对比度低、亮度较暗、细节缺失等问题,为此提出一种基于同态频分聚合的低照度图像增强算法。首先,改进同态滤波的传递函数,将原始图像分解为高频和低频分量,在不损失亮区细节的同时,增强一部分暗区细节,改进后的同态滤波传递函数参数更少,且易于调整;然后,分别对两个分量进行增强,即设计细节增强网络完善高频部分的细节信息,采用low-light image enhancement via illumination map estimation(LIME)算法对低频部分进行亮度提升;最后,设计局部自适应网络对图像高频和低频分量进行联合微调,纠正融合过程中出现的失真。从主观视觉以及客观评价指标两个方面进行实验分析,结果表明,所提算法能有效平衡图像平滑区域与纹理分量的增强效果,提升图像视觉质量。

A weak-light environment leads to low contrast,dark brightness,missing details,and other problems with pictures captured by image acquisition equipment.Therefore,a low illumination image-enhancement algorithm based on homomorphic frequency division aggregation is proposed.First,the transfer function of homomorphic filtering is improved,the original image is decomposed into high-and low-frequency components,and some dark-area details are enhanced without the loss of bright-area details.The improved homomorphic-filtering transfer function has fewer parameters than the original and is easy to adjust.Next,the two components are enhanced.That is,the detail enhancement network is designed to improve the detailed information of the high-frequency part,and the low-light image enhancement via illumination map estimation(LIME)algorithm is used to enhance the brightness of the low-frequency part.Finally,a local adaptive network is designed to jointly fine-tune the high-and low-frequency components of the image to correct the distortion during fusion.The experimental results from the subjective vision and objective evaluation indicators show that the proposed algorithm can effectively balance the enhancement effect of smooth regions and texture components of the image and improve the image visual quality.