For the past few years, image fusion technology has made great progress, especially in infrared and visible light image infusion. However, the fusion methods, based on traditional or deep learning technology, have some disadvantages such as unobvious structure or texture detail loss. In this regard, a novel generative adversarial network named MSAt-GAN is proposed in this paper. It is based on multi-scale feature transfer and deep attention mechanism feature fusion, and used for infrared and visible image fusion. First, this paper employs three different receptive fields to extract the multi-scale and multi-level deep features of multi-modality images in three channels rather than artificially setting a single receptive field. In this way, the important features of the source image can be better obtained from different receptive fields and angles, and the extracted feature representation is also more flexible and diverse. Second, a multi-scale deep attention fusion mechanism is designed in this essay. It describes the important representation of multi-level receptive field extraction features through both spatial and channel attention and merges them according to the level of attention. Doing so can lay more emphasis on the attention feature map and extract significant features of multi-modality images, which eliminates noise to some extent. Third, the concatenate operation of the multi-level deep features in the encoder and the deep features in the decoder are cascaded to enhance the feature transmission while making better use of the previous features. Finally, this paper adopts a dual-discriminator generative adversarial network on the network structure, which can force the generated image to retain the intensity of the infrared image and the texture detail information of the visible image at the same time. Substantial qualitative and quantitative experimental analysis of infrared and visible image pairs on three public datasets show that compared with state-of-the-art fusion methods, the proposed MSAt-GAN network has comparable outstanding fusion performance in subjective perception and objective quantitative measurement.
Regarding the problems of image distortion, edge blurring, Gibbs phenomena in the traditional wavelet transform algorithm and the loss of subtle features in the Non-Subsampled Shearlet Transform (NSST), and considering the physical characteristics of infrared and visible images, an infrared and visible image fusion algorithm based on the Lifting Stationary Wavelet Transform (LSWT) and Non-Subsampled Shearlet Transform is proposed in this paper. First, since LSWT can quickly calculate and has all advantages of traditional WT, it is utilized to decompose infrared and visible images to obtain lowfrequency coefficients and multi-scale and multi-directional high-frequency coefficients, respectively. Second, NSST multi-scale decomposition is used to extract the target features and detailed features of the image from the high and low-frequency sub-bands to obtain new high and low-frequency sub-bands. Third, according to the physical characteristics that low and high-frequency coefficients represent, different fusion rules are designed. Discrete Cosine Transform (DCT) and Local Spatial Frequency (LSF) are introduced in the low-frequency sub-band, and LSF adaptive weighted fusion rules are used in the DCT domain. The fusion strategy improves the regional contrast in the high-frequency sub-band with the spectral characteristics of human vision. Finally, the Inverse Lifting Stationary Wavelet Transform (ILSWT) is used to reconstruct the fusion coefficients to obtain the final fused images. To verify the advantages of the proposed algorithm in this paper, the classic and advanced 9 IR and VI fusion algorithms are selected for subjective and objective comparison. In the objective evaluation, a comprehensive ranking index is designed based on 9 classical indicators. Simulation experiments with 10 IR and VI fusion algorithms prove that the proposed algorithm has better performance and flexibility. The results show that the proposed algorithm in this paper fuses the images with clear edges, prominent targets, and good visual perception, and it outperforms state-of-the-art image fusion algorithms.
Most of the significant petroleum- and coal-bearing sedimentary basins in Northeast Asia originated via rifting and thermal subsidence during the Late Jurassic-Early Cretaceous, followed by basin inversion in the Late Cretaceous. However, the tectonic background governing these basin prototype shifts has not been fully explored. The unconformities are excellent archives of plate boundary interactions and geodynamic switches in subduction zones. The Eastern Heilongjiang Province (EHLJ), Northeast China (NE China), comprises a series of Mesozoic-Cenozoic residual basins with well-preserved successions and provides significant insights into the tectonic characteristics and background of Northeast Asia. Mesozoic unconformities and large-scale contractional structures in the basins mark a series of important tectonic transitions in Northeast Asia. Based on the synthesis information of regional Mesozoic unconformities identified in the seismic reflection profiles and field outcrops of EHLJ, the tectonic characteristics and geodynamic background of the Mesozoic continental margin basins in Northeast Asia are analysed. The Middle-Upper Jurassic/basement unconformity (U1) can only be found in some areas of the Sanjiang and Hulin basins. It was a response to the continental collision of Siberia and the northern China–Mongolia tract along the Mongolia–Okhotsk suture during the Jurassic. The Paleo-Pacific Plate rapidly subducted in the NNW direction towards the eastern margin of Eurasia in the early Lower Cretaceous resulting in a mass of strike-slip faults and the widespread absence of deposits (Valanginian) (U2) in the EHLJ. Because of the subduction slab rollback of the Paleo-Pacific Plate during the late Lower Cretaceous, the local asthenospheric material upwelled, and fault and volcanic activities intensified in Northeast Asia. The Lower Cretaceous Dongshan Formation (Fm)/Muleng Fm unconformity (U3-1) reflects a specific scale of bimodal magmatism in the Songliao Basin and the EHLJ. The Pacific Plate subducted in a transformation from NNW to WNW during the early Upper Cretaceous (Cenomanian). The Houshigou Fm (Qixinhe Fm)/Lower Cretaceous angular unconformity (U3) reflects that on the basins experienced denudation after being extensively uplifted from the subduction events. With the subduction of the Kula Plate, a compression stress field during the later Upper Cretaceous Period controlled NE China. The basins underwent a widely compressive deformation, accompanied by large-scale thrusts, denudation and deplanation, resulting in Paleogene/Cretaceous unconformity (U4) was formed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.