基于自适应阈值和局部色调映射的低照度图像处理  

Low Illumination Image Processing Based on Adaptive Threshold and Local Tone Mapping

作　　者：曹红燕 刘长明[1] 沈小林[1] 李大威[1] 陈燕 Cao Hongyan;Liu Changming;Shen Xiaolin;Li Dawei;Chen Yan(School of Electrical and Control Engineering,North University of China,Taiyuan,Shanxi 030051,China;Military Representative Office of Military Equipment Department in Beijing,Taiyuan,Shanxi 030051,China)

机构地区：[1]中北大学电气与控制工程院,山西太原030051 [2]陆军装备部驻北京地区军事代表局某军代室,山西太原030051

出　　处：《激光与光电子学进展》2021年第4期219-226,共8页Laser & Optoelectronics Progress

基　　金：山西省自然科学基金(201901D111151)。

摘　　要：为了解决低照度图像的细节信息缺少和清晰度低的问题,在HSV(Hue,Saturation,Value)色彩空间中,采用非下采样剪切波变换(NSST)与Retinex理论的融合算法对低照度图像进行处理。首先对HSV空间的V分量进行分解,得到多个高通子带与一个低通子带,对高通子带采用改进的基于贝叶斯萎缩的自适应阈值算法完成去噪,对低通子带采用改进的自适应局部色调映射算法提高对比度,然后对两个子带进行NSST逆变换以得到新的V分量并对其进行白平衡处理,最后将处理后的图像反转到RGB(Red,Green,Blue)空间中得到结果图像。实验结果表明,所提算法能够改善低照度图像的质量,提高清晰度与对比度。In order to solve the problem of lack of detailed information and low definition of low illuminance images,the fusion algorithm of non-undersampled shear wave transform(NSST)and Retinex theory is used to process low illuminance images in the color space of HSV(Hue,Saturation,Value).First,the V component of the HSV space is decomposed to obtain multiple high pass subbands and a low pass subband.The high pass subbands with the improved adaptive threshold algorithm based on Bayesian shrinkage denoising,the low pass subbands with the improved adaptive local color mapping algorithm improve the contrast.Then,the NSST inverse transformation is applied to the two subbands to obtain the new V components and white balance treatment is performed on them.Finally,the processed image is reversed to the RGB(Red,Green,Blue)space to get the result image.Experimental results show that the proposed algorithm can improve the quality of low illuminance images,and improve the definition and contrast.

关 键 词：图像处理 非下采样剪切波变换 图像去噪 HSV颜色空间 图像增强 RETINEX理论 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]