基于HSV色彩空间的低照度图像增强

Low-light image enhancement based on HSV color space

为解决低照度图像色彩偏暗、整体亮度较低、光照不均等问题,提出一种低照度图像增强算法。在HSV色彩空间将V分量按照灰度等级的高低进行分层处理,利用引入权重值的巴特沃斯滤波器对低灰度等级的V分量进行灰度级拉伸,利用提出的亮度控制方法对过度增强区域进行灰度级新映射,合并所有V分量并平滑,基于权重值和映射函数,提出S分量的自适应增强函数对图像色彩进行调整。实验结果表明,该算法是一种有效的低照度图像增强算法。

To address the problems in low-light images,such as dark color,low overall brightness and uneven brightness,a low-light image enhancement algorithm was proposed.In HSV color space,the V component was layered according to the gray level.The V components of low gray level were stretched using Butterworth filter with weight value,and the gray level remapping was performed on the over-enhanced area using the proposed brightness control method,all V components were then fused and smoothed.Based on the weight value and mapping function,an adaptive enhancement function for the S component was proposed to adjust the image color.The final experimental results show that the proposed algorithm is an effective low-light image enhancement algorithm.