基于半逆法的彩色图像光晕快速消除方法
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摘要
传统的彩色图像光晕消除方法计算量过大,各个环节之间衔接不够紧密,导致消除过程慢,消除结果差。为了解决此问题,基于半逆法研究了一种新的彩色图像光晕消除方法,对消除过程进行了重点设计,并对每一步进行阐述。在消除彩色图像光晕之前,首先要估算彩色图像背景颜色,分析各个颜色参量,然后找出产生光晕的局部区域,调节颜色对比度,接着通过控制系统和异常应对系统消除彩色图像的光晕,最后对图像上含有光晕的区域做颜色恢复处理。与传统消除方法进行实验对比,结果表明,基于半逆法的彩色图像光晕消除方法能够简化计算量,提高消除过程,改善消除结果。本研究对于图像处理有重要的指导意义。
The traditional method of color image halo elimination has too much calculation,and the links between the links are not close enough,resulting in slow elimination process and poor results. In order to solve this problem,a new halo elimination method of color image based on semi-inverse method is studied. The process of halo elimination is designed and each step is described. Before eliminating the halo of the color image,the background color of the color image should be estimated,and the color parameters should be analyzed. Then the local area of the halo should be found out,and the color contrast can be adjusted. Then the halo of the color image can be eliminated by the control system and the abnormal coping system. Finally,the area containing the halo in the image should be restored. Complex treatment. The experimental results show that the halo elimination method based on semi-inverse method can simplify the calculation,improve the elimination process and improve the results. This study has important guiding significance for image processing.
The traditional method of color image halo elimination has too much calculation,and the links between the links are not close enough,resulting in slow elimination process and poor results. In order to solve this problem,a new halo elimination method of color image based on semi-inverse method is studied. The process of halo elimination is designed and each step is described. Before eliminating the halo of the color image,the background color of the color image should be estimated,and the color parameters should be analyzed. Then the local area of the halo should be found out,and the color contrast can be adjusted. Then the halo of the color image can be eliminated by the control system and the abnormal coping system. Finally,the area containing the halo in the image should be restored. Complex treatment. The experimental results show that the halo elimination method based on semi-inverse method can simplify the calculation,improve the elimination process and improve the results. This study has important guiding significance for image processing.
引文
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[3]王晓红,王禹琛.基于双边滤波的自适应彩色图像去噪研究[J].包装工程,2017,38(15):168-172.
[4]贺炜.多维彩色图像特征快速抽取方法仿真研究[J].计算机仿真,2017,56(2):389-392.
[5]周千,李文胜.一种改进CB模型的彩色图像混合噪声去除方法[J].计算机与数字工程,2017,45(1):147-151.
[6]申春辉,郭陈凤,周罗岚.一种基于颜色恒常性的低照度图像增强方法[J].包装工程,2017,56(3):134-138.
[7]温阳,夏小妹,杨琳.基于视觉注意的全参考彩色图像质量评价方法[J].计算机测量与控制,2017,25(6):279-281.
[8]李延哲,梁仁鹏,张紫砚,等.基于DCT-DWTSVD的彩色图像安全存储方案[J].物联网技术,2017,7(5):59-62.
[9]赵红,魏勇刚,杨刚.一种基于alpha通道的彩色图像超分辨率方法[J].河北大学学报:自然科学版,2018,38(3):321-326.
[10]王金伟,刘仁峰.基于QDCT马尔科夫方法的彩色图像拼接检测[J].应用科学学报,2017,35(6):754-762.
[11]李宁,许树成,邓中亮.基于HSI色彩坐标相似度的彩色图像分割方法[J].现代电子技术,2017,40(2):30-33.
[12]李雨,方怡,王振东,等.基于空间域噪声检测的彩色图像缩放增强方法[J].岭南师范学院学报,2017,11(6):98-102.
[13]任荣梓,高航.基于混沌置乱的分量融合图像加密压缩方法[J].计算机技术与发展,2017,27(8):106-109.
[14]楼申龙,虞中捷.基于FSIM和不同颜色模型的彩色图像评价方法研究[J].电脑知识与技术,2017,13(7):226-228.
[15]吴海兵,张良,顾国华,等.基于低照度三基色图像去噪及融合彩色图像增强方法研究[J].应用光学,2018,56(1):57-63.
[16]王瑜,闫沫.基于Wasserstein距离和分裂Bregman方法的图像分割算法[J].电子设计工程,2017,25(2):140-144.