Synthetic aperture radar (SAR) change detection provides a powerful tool for continuous, reliable, and objective observation of the Earth, supporting wide range applications that require regular monitoring assessment changes in natural built environment. In this paper, we introduce novel SAR image method based on principal component analysis two-level clustering. First, two difference images log-ratio mean-ratio operators are computed, then fusion model is used to fuse images, new generated....

Aiming at the problems of a long design period and imperfect surrogate modeling in field airfoil optimization, convolutional neural network framework for performance prediction (DPCNN) is established based on deep learning method. The profile parameterization, physical prediction, are achieved. results show that DPCNN can generate substantial perfect profiles with only three geometric parameters. It has significant advantages such as good robustness, great convergence, fast computation...

In the field of remote sensing, due to memory consumption and computational burden, single-image super-resolution (SISR) methods based on deep convolution neural networks (CNNs) are limited in practical application. To address this problem, we propose a lightweight feature enhancement network (FeNet) for accurate remote-sensing image (SR). Considering existence equipment with extremely poor hardware facilities, further design lighter FeNet-baseline about 158K parameters. Specifically,...

Multi-focus image fusion plays an important role in the application of computer vision. In process fusion, there may be blurring and information loss, so it is our goal to obtain high-definition information-rich images. this paper, a novel multi-focus method via local energy sparse representation shearlet domain proposed. The source images are decomposed into low- high-frequency sub-bands according transform. low-frequency fused by representation, energy. inverse transform used reconstruct...

Poor illumination greatly affects the quality of obtained images. In this paper, a novel convolutional neural network named DEANet is proposed on basis Retinex for low-light image enhancement. combines frequency and content information images divided into three subnetworks: decomposition, enhancement, adjustment networks, which perform decomposition; denoising, contrast detail preservation; generation, respectively. The model trained public LOL dataset, experimental results show that it...

The fusion of infrared and visible images together can fully leverage the respective advantages each, providing a more comprehensive richer set information. This is applicable in various fields such as military surveillance, night navigation, environmental monitoring, etc. In this paper, novel image method based on sparse representation guided filtering Laplacian pyramid (LP) domain introduced. source are decomposed into low- high-frequency bands by LP, respectively. Sparse has achieved...

In this paper, we introduce an innovative approach to multi-focus image fusion by leveraging the concepts of fractal dimension and coupled neural P (CNP) systems in nonsubsampled contourlet transform (NSCT) domain. This method is designed overcome challenges posed limitations camera lenses depth-of-field effects, which often prevent all parts a scene from being simultaneously focus. Our proposed technique employs CNP with local topology-based model merge low-frequency components effectively....

In the realm of maritime target detection, infrared imaging technology has become predominant modality. Detecting small ships on sea surface is crucial for national defense and security. However, challenge detecting targets persists, especially in complex scenes surface. As a response to this challenge, we propose MAPC-Net, an enhanced algorithm based existing network. Unlike conventional approaches, our method focuses addressing intricacies sparse pixel occupancy ships. MAPC-Net...

Change detection is an important task in identifying land cover change different periods. In synthetic aperture radar (SAR) images, the inherent speckle noise leads to false changed points, and this affects performance of detection. To improve accuracy detection, a novel automatic SAR image algorithm based on saliency convolutional-wavelet neural networks proposed. The log-ratio operator adopted generate difference image, reducing anisotropic diffusion used enhance original multitemporal...

Multimodal medical image fusion aims to fuse images with complementary multisource information. In this paper, we propose a novel multimodal method using pulse coupled neural network (PCNN) and weighted sum of eight-neighborhood-based modified Laplacian (WSEML) integrating guided filtering (GIF) in non-subsampled contourlet transform (NSCT) domain. Firstly, the source are decomposed by NSCT, several low- high-frequency sub-bands generated. Secondly, PCNN-based rule is used process...

Remote sensing image change detection is widely used in land use and natural disaster detection. In order to improve the accuracy of detection, a robust method based on nonsubsampled contourlet transform (NSCT) fusion fuzzy local information C-means clustering (FLICM) model introduced this paper. Firstly, log-ratio mean-ratio operators are generate difference (DI), respectively; then, NSCT utilized fuse two images, one new DI obtained. The fused can not only reflect real trend but also...

To solve problems of brightness and detail information loss in infrared visible image fusion, an effective fusion method using rolling guidance filtering gradient saliency map is proposed this paper. The used to decompose the input images into approximate layers residual layers; energy attribute model fuse introduced corresponding weight matrices are constructed perform on layers. generated by reconstructing fused layer sub-image sub-images. Experimental results demonstrate superiority method.

The automatic monitoring and detection of maritime targets hold paramount significance in safeguarding national sovereignty, ensuring rights, advancing development. Among the principal means surveillance, infrared (IR) small ship technology stands out. However, due to their minimal pixel occupancy lack discernible color texture information, IR ships have persistently posed a formidable challenge realm target detection. Additionally, intricate backgrounds often exacerbate issue by inducing...

Multi-focus image fusion is an important method for obtaining fully focused information. In this paper, a novel multi-focus based on fractal dimension (FD) and parameter adaptive unit-linking dual-channel pulse-coupled neural network (PAUDPCNN) in the curvelet transform (CVT) domain proposed. The source images are decomposed into low-frequency high-frequency sub-bands by CVT, respectively. FD PAUDPCNN models, along with consistency verification, employed to fuse sub-bands, average used...

In recent years, with the increasingly serious problems of resource shortage and environmental pollution, exploration development underwater clean energy were particularly important. At same time, abundant resources species have attracted a large number scientists to carry out research on underwater-related tasks. Due diversity complexity environments, it is difficult perform related vision tasks, such as target detection capture. The digital image technology has been relatively mature,...

Summary The eukaryotic DNA mismatch repair (MMR) system contributes to maintaining genome integrity and sequence fidelity in at least two important ways: by correcting errors arising during replication, also preventing recombination events between divergent sequences. This study aimed investigate the role of one key MMR gene recombination. We obtained a mutant line which AtMLH1 has been disrupted insertion T‐DNA within coding region. Transcript analysis indicated that no full‐length...

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the constructed based on idea of basic algorithm, which divide whole into many subscheduling problems and then NEH heuristic be introduced to solve problem. Secondly, some subsequences are operated with certain probability in pulse emission loudness phases. An intensive virtual population neighborhood search integrated further improve performance. Finally, experimental results...

Porcine reproductive and respiratory syndrome (PRRS), which is caused by PRRS virus (PRRSV), of great economic significance to the swine industry. Due complicated immune escape mechanisms PRRSV, there are no effective vaccines or therapeutic drugs currently available against PRRS. Identification cellular factors underlying that establish an antiviral state PRRSV can provide unique strategies for developing drugs. As interferon (IFN)-stimulated gene, role IFN-induced transmembrane 3 (IFITM3)...