摘要
水下机器人仅通过传统光学相机获取图像很难在复杂水下环境中或目标物具有保护色的情况下检测到目标,而通过高光谱技术进行水下目标检测可以改善这一情况;由于直接运用传统高光谱检测方法难以满足水下机器人对水下目标检测的要求,提出了一种基于最佳邻域重构指数(ONRIF)的高光谱目标检测方法,该方法通过线性重构的思想进行邻域寻优,选出信息量高且波段相关性低的波段组合,并使用所选波段的融合图像进行目标检测;结果表明,与直接对原始水下海产品高光谱图像进行检测相比,该方法在保证检测效果的前提下,大量减少了检测时间和数据冗余程度;还提出了一种在相同环境下对同类目标物的单波段快速采集检测方法,大大提高了采集数据的速度,可以满足水下机器人对海产品检测的需求。
It is difficult for underwater robots to detect targets in complex underwater environments or when the targets have protective colors only by acquiring images through conventional optical cameras,and underwater target detection by hyperspectral techniques can improve this situation.Since it is difficult to meet the requirements of underwater robot for underwater target detection by directly applying traditional hyperspectral detection methods,a hyperspectral target detection method based on optimal neighborhood reconstruction index factor(ONRIF)is proposed,which performs neighborhood search by the idea of linear reconstruction,selects a combination of bands with high information content and low band correlation,and uses the fused image of the selected bands for target detection.Compared with direct detection,this method substantially reduces the detection time and data redundancy while ensuring the detection effect.A single-band fast acquisition detection method for similar targets in the same environment is also proposed,which greatly improves the speed of data acquisition and can meet the needs of underwater robots for seafood detection.
作者
李斯特
孙旭东
张红旗
徐凤强
付先平
LI Site;SUN Xudong;ZHANG Hongqi;XU Fengqiang;FU Xianping(School of Information Science and Technology,Dalian Maritime University,Dalian 116026,China;Pengcheng Laboratory,Shenzhen 518033,China)
出处
《计算机测量与控制》
2021年第10期38-44,49,共8页
Computer Measurement &Control
基金
国家自然科学基金(61802043,61370142,61272368)
兴辽英才计划(XLYC1908007)
大连市科技创新项目(2018J12GX037,2019J11CY001)
中央高校基本科研业务费专项基金(3132016352,3132019203,3132020215)。
关键词
水下机器人
高光谱图像
水下高光谱检测
最佳邻域重构指数(ONRIF)
波段组合
underwater robots
hyperspectral images
underwater hyperspectral detection
optimal neighborhood reconstruction index factor(ONRIF)
band combination