摘要
针对复杂海面地貌、云雾背景下的光学遥感图像舰船目标检测问题,提出一种结合空域和频域视觉显著性特征的无监督舰船目标检测算法。基于图像的RGB颜色空间和ITTI模型,利用图像亮度特征图、颜色特征图、亮度特征的一阶梯度组合构建图像特征,并基于图像区域与整幅图像的协方差矩阵计算图像区域的差异性。然后由协方差矩阵之间的广义特征值构建空域显著特征图,并加入PQFT(phasespectrum of quaternion Fourier transform)模型的频域显著特征图。最后利用元胞自动机融合空域显著特征和频域显著特征。实验结果表明,所提算法检测舰船目标时的性能要优于其他常用的视觉显著算法。
To address the problem of ship target detection in optical remote sensing images under complex sea surface landform and cloud background conditions,an unsupervised ship target detection algorithm that combines the visual salient features of spatial and frequency domains is proposed.First,based on the RGB color space and the ITTI model of the images,image features are constructed using a combination of image brightness feature map,color feature map,and one-step brightness feature.Moreover,the regional difference in the image is calculated using the covariance matrix of the image region and the entire image.Further,the spatial-domain salient feature map is constructed using the generalized eigenvalue of the covariance matrix,and the frequency-domain salient feature map of the phase spectrum of quaternion Fourier transform(PQFT)model is added.Finally,the spatial-and frequency-domain salient features are combined using cellular automata.The experimental results show that the proposed algorithm is superior to other visual salient algorithms commonly used for ship target detection.
作者
黎经元
厉小润
赵辽英
Li Jingyuan;Li Xiaorun;Zhao Liaoying(College of Electrical Engineering,Zhejiang University,Hangzhou,Zhejiang 310027,China;Institute of Computer Application Technology,Hangzhou Dianzi University,Hangzhou,Zhejiang 310018,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2021年第4期349-357,共9页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61671408)
教育部联合基金(6141A02022350)
省级重点研发计划(209C05004)。
关键词
机器视觉
光学遥感图像
无监督舰船检测
改进CovSal算法
PQFT算法
元胞自动机
machine vision
optical remote sensing image
unsupervised ship detection
improved CovSal algorithm
phase spectrum of quaternion Fourier transform algorithm
cellular automata
