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首页>《中国测试》期刊>本期导读>基于形态和小波的低纹理图序列高光修复研究

基于形态和小波的低纹理图序列高光修复研究

100    2019-04-28

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作者:唐露新1, 张宇维1, 宋有聚2, 王小桂3, 于丽敏1

作者单位:1. 广东工业大学机电工程学院, 广东 广州 510006;
2. 深圳市施罗德工业测控设备有限公司, 广东 深圳 518055;
3. 深圳市一零江苏快三开奖有限公司, 广东 深圳 518055


关键词:低纹理;形态学重建;小波变换;高光修复


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 of low texture image sequences restoration based on morphological reconstruction and wavelet transform
TANG Luxin1, ZHANG Yuwei1, SONG Youju2, WANG Xiaogui3, YU Limin1
1. Guangdong University of Technology, Guangdong, Guangzhou 510006, China;
2. Shenzhen Srod Robotics Industrial Measurement and Control Equipment Co., Ltd., Shenzhen 518055, China;
3. Shenzhen Srod One Zero Science and Technology Service Co., Ltd., Shenzhen 518055, China
Abstract: 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%.
Keywords: low texture;morphological reconstruction;wavelet transform;highlight restoration
2019, 45(4):109-115  收稿日期: 2018-10-20;收到修改稿日期: 2018-11-15
基金项目:
作者简介: 唐露新(1958-),男,湖南冷水江市人,教授,硕士,研究方向为图像检测与信号处理、传感器网络与测控、无人机技术与定位、精密仪器与测控系统、舞台灯光技术与控制、机电一体化技术
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