We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractiona...We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.展开更多
高光谱图像异常检测作为一种无监督的目标检测,主要存在异常目标类型多样化、异常与背景不易区分、以及检测精度受场景影响大等难题。针对以上问题,本文提出了一种基于空谱多路自编码器的高光谱图像异常检测方法。首先,提出一种加权空谱...高光谱图像异常检测作为一种无监督的目标检测,主要存在异常目标类型多样化、异常与背景不易区分、以及检测精度受场景影响大等难题。针对以上问题,本文提出了一种基于空谱多路自编码器的高光谱图像异常检测方法。首先,提出一种加权空谱Gabor滤波方法,提取高光谱图像的多尺度空谱特征;其次,采用多路自编码器降低多尺度空谱特征在光谱维的冗余度,提取空谱特征中的主要信息;最后,利用得到的主要空谱特征,结合形态学滤波与双曲正切函数进行特征增强,以提高异常与背景噪声的区分度。本文提出的方法是一种即插即用的异常检测方法,无需额外的参数输入;多路自编码器提取了多尺度主要空谱特征,以应对异常目标类型多样化的难题;通过特征增强提高了背景与异常的区分度。将本文提出的方法与9种流行的异常检测方法相比,在5个高光谱数据集上进行验证,通过对比异常检测结果图、接收机操作特性(Receiver Operating Characteristic,ROC)曲线、ROC曲线下覆盖的面积AUC(Area Under Curve)以及异常像元与背景像元的箱型图等评价指标,证明了本文方法优于其他9种方法。展开更多
基金supported by national natural science foundation of China(No.41274127,41301460,40874066,and 40839905)
文摘We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.
文摘高光谱图像异常检测作为一种无监督的目标检测,主要存在异常目标类型多样化、异常与背景不易区分、以及检测精度受场景影响大等难题。针对以上问题,本文提出了一种基于空谱多路自编码器的高光谱图像异常检测方法。首先,提出一种加权空谱Gabor滤波方法,提取高光谱图像的多尺度空谱特征;其次,采用多路自编码器降低多尺度空谱特征在光谱维的冗余度,提取空谱特征中的主要信息;最后,利用得到的主要空谱特征,结合形态学滤波与双曲正切函数进行特征增强,以提高异常与背景噪声的区分度。本文提出的方法是一种即插即用的异常检测方法,无需额外的参数输入;多路自编码器提取了多尺度主要空谱特征,以应对异常目标类型多样化的难题;通过特征增强提高了背景与异常的区分度。将本文提出的方法与9种流行的异常检测方法相比,在5个高光谱数据集上进行验证,通过对比异常检测结果图、接收机操作特性(Receiver Operating Characteristic,ROC)曲线、ROC曲线下覆盖的面积AUC(Area Under Curve)以及异常像元与背景像元的箱型图等评价指标,证明了本文方法优于其他9种方法。
