摘要
针对低照度彩色图像存在亮度低、对比度差等问题提出一种自适应低照度彩色图像增强算法。该算法先将RGB图像转换为HSV图像,设计新颖的目标函数,利用樽海鞘群算法优化伽马变换参数。然后对亮度通道依次进行自适应伽马变换和引导滤波算法增强图像的亮度和对比度,最后通过8组不同低照度图像的仿真实验并与多种算法进行比较,结果:该算法在熵值、亮度、对比度和梯度方面优势明显。
Aimed at the problems such as low brightness and poor contrast in low lightening color images,an adaptive low lightening color image enhancement algorithm is proposed in this paper.This algorithm first converts RGB image to HSV image,designs the novel objective function,optimizes gamma parameters by salp swarm algorithm,then performs gamma transform in turn on adaptive brightness channel and guides filtering algorithm to enhance the brightness and contrast of the image.At last,through eight different sets of low lightening image simulation experiments and compared with many kinds of algorithms,the results show that the proposed algorithm has obvious advantages in entropy,brightness,contrast and gradient.
作者
程晶晶
CHENG Jing-jing(Anhui Technical College of Mechanical and Electrical Engineering,Wuhu 241000,China)
出处
《南宁师范大学学报（自然科学版）》
2023年第3期51-56,共6页
Journal of Nanning Normal University：Natural Science Edition
基金
安徽高校自然科学研究项目重点项目(KJ2020A1115)
安徽省高校优秀青年人才支持计划重点项目(gxyqZD2019106)
提质培优行动计划项目(2020tzpy1801-3)
安徽省教学研究项目(2020jyxm0316)。
关键词
低照度
伽马变换
图像增强
引导滤波
樽海鞘群算法
low lightening
gamma transformtion
image enhancement
guide filtering
salp swarm algorithm
