| Related citation: | Hao Li,Jianguo Tao,Yang Luo,Liping Deng,Zongquan Deng.An Underwater Image Bubble Noise Removal Method Based on Optical Flow[J].Journal of Harbin Institute Of Technology(New Series),2019,26(1):11-16.DOI:10.11916/j.issn.1005-9113.18091. |
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| Author Name | Affiliation | | Hao Li | State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China | | Jianguo Tao | State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China | | Yang Luo | State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China | | Liping Deng | State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China | | Zongquan Deng | State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: |
| It is very important for underwater robots to accurately detect and locate target objects. However, under many circumstances, it is difficult to clearly observe the target object due to the existence of bubble noise. In this paper, we proposed a method to solve this problem. First, we used the LK optical flow algorithm to calculate the motion vector of the image background and compensate for the background motion. Then, the optical flow field of the bubbles was calculated by the HS optical flow algorithm, and the area where the bubble existed was obtained by binarizing the image. Finally, we used the adjacent frame image to repair the bubble area. We carried out a bubble noise removal experiment. The results show that this method can effectively remove the bubble noise in the image. |
| Key words: bubble noise optical flow background motion image repair |
| DOI：10.11916/j.issn.1005-9113.18091 |
| Clc Number:TH-39 |
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| Descriptions in Chinese: |
| 基于光流法的水下图像气泡噪声消除方法 李浩，陶建国，罗阳，邓立平，邓宗全 （哈尔滨工业大学 机器人与系统国家重点实验室，哈尔滨 150001） 中文说明：对于水下机器人来说，准确地检测和定位目标物体是非常重要的。 然而，在许多情况下，由于存在气泡噪声，很难清楚地观察目标物体。本文提出一种基于光流法的水下图像气泡噪声消除方法。 首先使用LK光流算法计算图像背景的运动矢量并补偿背景运动。 然后，通过HS光流算法计算气泡的光流场，并通过二值化图像获得气泡存在的区域。 最后使用相邻的帧图像来修复气泡区域。气泡噪声去除实验结果表明，该方法可有效去除图像中的气泡噪声。 关键词：气泡噪声，光流法，背景运动，图像修复 |
