To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability...To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.展开更多
The change detection(CD)of heterogeneous remote sensing images is an important but challenging task.The difficulty is to obtain the change information by directly comparing the different statistical characteristics of...The change detection(CD)of heterogeneous remote sensing images is an important but challenging task.The difficulty is to obtain the change information by directly comparing the different statistical characteristics of the images acquired by different sensors.This paper proposes an unsupervised method for heterogeneous image CD based on an image domain transfer network.First,an attention mechanism is added to the Cycle-generative adversarial networks(Cycle-GANs)to obtain a more consistent feature expression by transferring bi-temporal heterogeneous images to the common domain.The Euclidean distance of the corresponding pixels is calculated in the common domain to form a difference map,and a threshold algorithm is applied to get a rough change map.Finally,the proposed adaptive Discrete Cosine Transform(DCT)algorithm reduces the noise introduced by false detection,and the final change map is obtained.The proposed method is verified on three real heterogeneous CD datasets and compared with the current state-of-the-art methods.The results show that the proposed method is accurate and robust for performing heterogeneous CD tasks.展开更多
文摘To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.
基金supported by Military Commission Science and Technology Committee Leading Fund of China:[Grant Number 18-163-00-TS-004-080-01].
文摘The change detection(CD)of heterogeneous remote sensing images is an important but challenging task.The difficulty is to obtain the change information by directly comparing the different statistical characteristics of the images acquired by different sensors.This paper proposes an unsupervised method for heterogeneous image CD based on an image domain transfer network.First,an attention mechanism is added to the Cycle-generative adversarial networks(Cycle-GANs)to obtain a more consistent feature expression by transferring bi-temporal heterogeneous images to the common domain.The Euclidean distance of the corresponding pixels is calculated in the common domain to form a difference map,and a threshold algorithm is applied to get a rough change map.Finally,the proposed adaptive Discrete Cosine Transform(DCT)algorithm reduces the noise introduced by false detection,and the final change map is obtained.The proposed method is verified on three real heterogeneous CD datasets and compared with the current state-of-the-art methods.The results show that the proposed method is accurate and robust for performing heterogeneous CD tasks.
