An ISAR and Visible Image Fusion Algorithm Based on Adaptive Guided Multi-Layer Side Window Box Filter Decomposition DOI Creative Commons
Jiajia Zhang, Huan Li, Dong Zhao

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(11), P. 2784 - 2784

Published: May 26, 2023

Traditional image fusion techniques generally use symmetrical methods to extract features from different sources of images. However, these conventional approaches do not resolve the information domain discrepancy multiple sources, resulting in incompleteness fusion. To solve problem, we propose an asymmetric decomposition method. Firstly, abundance discrimination method is used sort images into detailed and coarse categories. Then, are proposed at scales. Next, strategies adopted for scale features, including sum fusion, variance-based transformation, integrated energy-based Finally, result obtained through summation, retaining vital both Eight metrics two datasets containing registered visible, ISAR, infrared were evaluate performance The experimental results demonstrate that could preserve more details than symmetric one, performed better objective subjective evaluations compared with fifteen state-of-the-art methods. These findings can inspire researchers consider a new framework adapt differences richness images, promote development technology.

Language: Английский

A fuzzy control algorithm based on artificial intelligence for the fusion of traditional Chinese painting and AI painting DOI Creative Commons

Xu Xu

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 1, 2024

Recently, artificial intelligence (AI)-generated resources have gained popularity because of their high effectiveness and reliability in terms output capacity to be customized broadened, especially image generation. Traditional Chinese paintings (TCPs) are incomplete color contrast is insufficient, object reality minimal. However, combining AI painting (AIP) with TCP remains inadequate uncertain features such as patterns, styles, color. Hence, an algorithm named variational fusion-based fuzzy accelerated (VF2AP) has been proposed resolve this challenge. Initially, the collected data source applied for preprocessing convert it into a grayscale image. Then, feature extraction process performed via fuzzy-based local binary pattern (FLBP) brushstroke patterns enhance fusion intelligent logic optimize textures noisy Second, extracted used inputs autoencoder (VAE), which avoid latent space irregularities reconstructed by maintaining minimum reconstruction loss. Third, inference rules variation original images. Fourth, feedback mechanism designed evaluation metrics area under curve-receiver operating characteristic (AUC-ROC) analysis, mean square error (MSE), structural similarity index (SSIM), Kullback‒Leibler (KL) divergence viewer's understanding fused

Language: Английский

Citations

6
Research on pedestrian detection method based on multispectral intermediate fusion using YOLOv7 DOI Creative Commons

Bo Jiang,

Jingyu Wang,

Guoyin Ren

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 15, 2025

Abstract This study is based on the YOLOv7 object detection framework and conducts comparative experiments early fusion, halfway late fusion for multispectral pedestrian tasks. Traditional tasks typically use image data from a single sensor or modality. However, in field of remote sensing, fusing multi-source crucial improving performance. aims to explore impact different strategies performance identify most suitable approach data. Firstly, we implemented by merging with visible light at network’s input layer. Next, were conducted, middle layers. Finally, performed high A comprehensive comparison experimental results various reveals that strategy exhibits outstanding tasks, achieving accuracy relatively fast speed.

Language: Английский

Citations

0
Infrared and Visible Image Fusion Using Multi-scale Decomposition and Partial Differential Equations DOI
Gargi Trivedi,

Rajesh Sanghvi

International Journal of Applied and Computational Mathematics, Journal Year: 2024, Volume and Issue: 10(4)

Published: July 2, 2024

Language: Английский

Citations

2
TransImg: A Translation Algorithm of Visible-to-Infrared Image Based on Generative Adversarial Network DOI Creative Commons
Shuo Han,

Bo Mo,

Junwei Xu

et al.

International Journal of Computational Intelligence Systems, Journal Year: 2024, Volume and Issue: 17(1)

Published: Oct. 23, 2024

Infrared images of sensitive targets are difficult to obtain and cannot meet the design training needs target detection tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation algorithm TransImg, which can achieve visible light infrared domain enrich dataset. First, designed a generator structure consisting deep residual connected encoder region perception feature fusion module enhance learning, thereby avoiding issues generating with insufficient details in transfer task. Afterward, multi-scale discriminator composite loss function were further improve effect. Finally, automatic mixed-precision strategy was overall migration architecture accelerate generation images. Experiments have shown that TransImg has good accuracy, generated by richer texture details, faster speed, lower video memory consumption, performance exceeds mainstream traditional algorithm, requirements

Language: Английский

Citations

2
ADF‐Net: Attention‐guided deep feature decomposition network for infrared and visible image fusion DOI Creative Commons
Sen Shen, Taotao Zhang,

Haidi Dong

et al.

IET Image Processing, Journal Year: 2024, Volume and Issue: 18(10), P. 2774 - 2787

Published: May 23, 2024

Abstract To effectively enhance the ability to acquire information by making full use of complementary features infrared and visible images, widely used image fusion algorithm is faced with challenges such as loss blurring. In response this issue, authors propose a dual‐branch deep hierarchical network (ADF‐Net) guided an attention mechanism. Initially, convolution module extracts shallow image. Subsequently, decomposition feature extractor introduced, where in transformer encoder block (TEB) employs remote process low‐frequency global features, while CNN (CEB) high‐frequency local information. Ultimately, layer based on TEB CEB produce fused through encoder. Multiple experiments demonstrate that ADF‐Net excels various aspects utilizing two‐stage training appropriate function for testing.

Language: Английский

Citations

1
Dual-branch network object detection algorithm based on dual-modality fusion of visible and infrared images DOI
Zhiqiang Hou, Xinyue Li, Yang Chen

et al.

Multimedia Systems, Journal Year: 2024, Volume and Issue: 30(6)

Published: Nov. 5, 2024

Language: Английский

Citations

1
Correlation reconstruction mechanism based on dual wavelength imaging and neural network DOI Creative Commons
Hualong Ye,

Daidou Guo

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 2, 2024

Language: Английский

Citations

1
Fusionfrfcm: An Image Fusion Approach Driven by Non-Global Fuzzy Pre-Enhancement Framework DOI
Xiangbo Zhang, Gang Liu, Lei Huang

et al.

Published: Jan. 1, 2024

Most of the existing image fusion models adopt a global strategy, which usually reduces contrast infrared images. In this paper, we propose an approach driven by non-global fuzzy pre-enhancement framework (FusionFRFCM), is more suitable for structure (IR) image. A equalization algorithm based on Fourth-order Partial Differential Equation (FPDE) proposed, used to enhance background region. Due differences between IR and visible (VIS) images, hybrid strategy Expectation Maximization (EM) Principal Component Analysis (PCA) designed. Compared with other state-of-the-art methods, experimental results show that proposed has better performance in both qualitative quantitative results. addition, verify effectiveness our FusionFRFCM practical application, embedded into RGBT target tracking task under VOT-RGBT2019 OTCBVS datasets. Through comparative experiments, it found can easily be integrated improve accuracy many scenes.

Language: Английский

Citations

0
GIAE-Net: A gradient-intensity oriented model for multimodal lung tumor image fusion DOI Creative Commons
Tao Zhou, Long Liu,

Huiling Lu

et al.

Engineering Science and Technology an International Journal, Journal Year: 2024, Volume and Issue: 54, P. 101727 - 101727

Published: June 1, 2024

Multimodal medical image fusion plays an important role in clinical applications. However, gradient features and intensity are not extracted inadequately methods. To solve the above problems, this paper proposes a Gradient-Intensity oriented Automatic Encode-Decode multimodal lung tumor model (GIAE-Net), there two parallel branches network, one is branch, another branch. The main idea of proposed network as follows:Firstly, attention module (GAM) designed to enhance description ability fine-grained spatial by using operators, so that can retain more edge details. Secondly, (IAM) constructed enable learn features, which highlight lesion region information. Thirdly, (GIFM) feature flow strategy designed. It converts problem into weight assignment extraction realized gradually. Finally, new dataset PET-CT established, contains 2575 pairs images (PCLset). experimental results on PCLset show compared with other nine models, achieve better performance. In CT window PET comparison experiment, SD, IE, AG, QAB/F, VIF EI indexes improved 20.38 %,7.70 %,16.44 %, 21.90 %,11.52 % 33.95 respectively.

Language: Английский

Citations

0
An effective reconstructed pyramid crosspoint fusion for multimodal infrared and visible images DOI

P. Murugeswari,

N. Kopperundevi,

M. Annalakshmi

et al.

Signal Image and Video Processing, Journal Year: 2024, Volume and Issue: 18(10), P. 6769 - 6782

Published: June 21, 2024

Language: Английский

Citations

0