基于形态和小波的低纹理图序列高光修复研究
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摘要
高光区域多出现于低纹理材料的平滑表面上,严重影响图像采集处理效果。针对现有图像去高光技术中过分依赖特定对象纹理特征的问题,该文提出一种利用形态学重建检测高光区域、利用小波变换修复高光区域低纹理图像序列的高光检测与抑制方法。对地下混凝土、金属等管道内壁表面高光区域进行修复,取得较好效果;通过修复胶合板等多种低纹理经典材质,对比其他方法,并应用差分图像的均值、方差与互相关系数评价修复效果。结果表明,修复后的多种材质与原图相似度在0.87以上,比其他方法的相似度平均提高9.7%与6.7%,且可同时应用于多种材料的高光区域处理,具有较好的应用前景。
Highlight region is mostly on the smooth surface with low texture, which seriously affects the effect of image acquisition. In view of the problem that the existing image sequence is overly dependent on the texture matching in highlight technology, a method of high light detection and suppression by using morphological reconstruction to detect highlight region and wavelet transform to repair low texture image sequence is proposed. The highlight area of the inner surface of pipes, such as concrete and metal, was repaired. At the same time, comparative experiments were carried out on various low texture materials, such as plywood. The mean, variance and correlation coefficient of difference images were used to evaluate the restoration. Results show that the similarity of different materials restored by this method is above 0.87, and the average increase of 9.7% and 6.7%.
Highlight region is mostly on the smooth surface with low texture, which seriously affects the effect of image acquisition. In view of the problem that the existing image sequence is overly dependent on the texture matching in highlight technology, a method of high light detection and suppression by using morphological reconstruction to detect highlight region and wavelet transform to repair low texture image sequence is proposed. The highlight area of the inner surface of pipes, such as concrete and metal, was repaired. At the same time, comparative experiments were carried out on various low texture materials, such as plywood. The mean, variance and correlation coefficient of difference images were used to evaluate the restoration. Results show that the similarity of different materials restored by this method is above 0.87, and the average increase of 9.7% and 6.7%.
引文
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[5]尹芳,陈田田,吴锐,等.均场退火算法在单幅灰度图像高光检测与恢复中的应用[J].计算机辅助设计与图形学学报,2017,29(5):829-837.
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[9]何嘉林,唐露新,林永强.基于融合技术的图像去高光方法[J].科学技术创新,2018(6):90-92.
[10]SAMAR M.ALSALEH,ANGELICA I,et al ReTouchImage:Fusioning from-local-to-global context detec-tion and graph data structures for fully-automatic specular reflection removal for endoscopic image[J].Computerized Medical Image and Graphics,2019,73(4):39-48.
[11]黄远程,宋博文.形态学重建与Canny结合实现机场跑道边界检测[J].遥感信息,2016,31(6):75-82.
[12]寇万里,车嵘,严丽娜.基于形态学重建和边界融合的视频对象分割方法研究[J].通信技术,2018,51(4):825-828.
[13]刘娇娇.基于小波变换和Harris算子的数字图像修复研究[D].大连:大连理工大学,2014.
[14]REHAM G,ELLA H A,HASSAN E B A,et al.Multi-spectral and panchromatic image fusion approach using stationary wavelet transform and swarm flower pollination optimization for remote sensing applications[J].Future Generation Computer Systems,2018,22(6):501-511.
[15]汤一平,鲁少辉,吴挺,等.基于主动式全景视觉的管道形貌缺陷检测系统[J].红外与激光工程,2016,45(11):183-189.
[16]邹玮刚,周志辉,王洋.基于非降采样轮廓波变换的图像修复算法[J].计算机应用,2017,37(2):553-558.