A Bi-Histogram Shifting Contrast Enhancement for Color Images

作     者：Lord Amoah Ampofo Twumasi Kwabena 

作者机构：Engineering Research Center of Digital ForensicsMinistry of EducationNanjing University of Information Science&TechnologyNanjing210044China School of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Department of Computer ScienceUniversity of Ghana-LegonAccra00233Ghana 

出 版 物：《Journal of Quantum Computing》 (量子计算杂志（英文）)

年 卷 期：2021年第3卷第2期

页      面：65-77页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the National Natural Science Foundation of China under Grant No.61662039 in part by the Jiangxi Key Natural Science Foundation under No.20192ACBL20031 in part by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology(NUIST)under Grant No.2019r070 in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Fund 

主　　题：Contrast enhancement bi-histogram shifting histogram equalization 

摘      要：Recent contrast enhancement(CE)methods,with a few exceptions,predominantly focus on enhancing gray-scale *** paper proposes a bi-histogram shifting contrast enhancement for color images based on the RGB(red,green,and blue)color *** proposed method selects the two highest bins and two lowest bins from the image histogram,performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked *** proposed method simultaneously performs both right histogram shifting(RHS)and left histogram shifting(LHS)in each histogram shifting repetition to embed and split the highest bins while combining the lowest bins with their neighbors to achieve histogram equalization(HE).The least maximum number of histograms shifting repetitions among the three RGB channels is used as the default number of histograms shifting repetitions performed to enhance original *** to an existing contrast enhancement method for color images and evaluated with PSNR,SSIM,RCE,and RMBE quality assessment metrics,the experimental results show that the proposed method s enhanced images are visually and qualitatively superior with a more evenly distributed *** proposed method achieves higher embedding capacities and embedding rates in all images,with an average increase in embedding capacity of 52.1%.