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Mamba Collaborative Implicit Neural Representation for Hyperspectral and Multispectral Remote Sensing image Fusion

ieee TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Zhu, Chunyu Deng, Shangqi Song, Xuan Li, Yachao Wang, Qi Xidian Univ Hangzhou Inst Technol Hangzhou 311231 Zhejiang Peoples R China Xi An Jiao Tong Univ Natl Key Lab Human Machine Hybrid Augmented Intell Natl Engn Res Ctr Visual Informat & Applicat Inst Artificial Intelligence & Robot Xian 710049 Shaanxi Peoples R China Northwestern Polytech Univ Sch Astronaut Xian 710072 Peoples R China Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

Hyperspectral remote sensing images (HSIs) capture detailed spectral characteristics of features, while multi- spectral remote sensing images (MSIs) provide clear spatial distribution. Fusing these two types of images can enhance feature identification and classification accuracy. Current deep learning algorithms achieve high fusion quality but struggle with balancing global effective perception and lightweight computation. Moreover, these algorithms typically discretely handle data mapping, which contrasts with the continuous nature of the world. Recently, the Mamba has shown significant potential for complex long-range modeling, addressing the computational complexity of global perception. Concurrently, implicit neural representation (INR) offers high-quality solutions for continuous domain modeling. To this end, this study introduces a novel network architecture that combines Mamba and INR, termed the Mamba cooperative INR fusion network (MCIFNet). MCIFNet effectively captures global image information and generates fused images in a continuous domain through pointto-point processing. The network comprises two main units: potential space projection and semantic extraction and fusion. The potential space projection unit performs shallow encoding of hyperspectral and MSIs, mapping them to a latent feature space. The semantic extraction and fusion unit (SEFU) uses scale adaptive residual state spatial and implicit spatial-spectral fusion (ISSF) modules to extract deep features from the bimodal images, generating fused images point-by-point. A series of fusion experiments with 4x, 8x, and 16x scale factors demonstrate that MCIFNet surpasses popular algorithms in both spatial detail and spectral information reconstruction, while also providing more lightweight performance. The code for MCIFNet will be shared on https://***/chunyuzhu/MCIFNet.

关键词： Feature extraction Accuracy Spatial resolution Matrix decomposition Optimization Deep learning Sparse approximation image fusion Hyperspectral imaging Transformers Hyperspectral and multispectral image fusion implicit neural representation (INR) Mamba Mamba cooperative INR fusion network (MCIFNet) state-space model (SSM)

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DX2CT: Diffusion Model for 3D CT Reconstruction from Bi or Mono-planar 2D X-ray(s)

DX2CT: Diffusion Model for 3D CT Reconstruction from Bi or M...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Yun Su Jeong Hye Bin Yoo Il Yong Chun Department of Electrical and Computer Engineering Sungkyunkwan University Republic of Korea Departments of Artificial Intelligence and Advanced Display Engineering Sungkyunkwan University Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science (IBS) Suwon Republic of Korea

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

computational tomography (CT) provides high-resolution medical imaging, but it can expose patients to high radiation. X-ray scanners have low radiation exposure, but their resolutions are low. This paper proposes a new conditional diffusion model, DX2CT, that reconstructs three-dimensional (3D) CT volumes from bi or mono-planar X-ray image(s). Proposed DX2CT consists of two key components: 1) modulating feature maps extracted from two-dimensional (2D) X-ray(s) with 3D positions of CT volume using a new transformer and 2) effectively using the modulated 3D position-aware feature maps as conditions of DX2CT. In particular, the proposed transformer can provide conditions with rich information of a target CT slice to the conditional diffusion model, enabling high-quality CT reconstruction. Our experiments with the bi or mono-planar X-ray(s) benchmark datasets show that proposed DX2CT outperforms several state-of-the-art methods. Our codes and model will be available at: https://***/intyeger/DX2CT.

关键词： Three-dimensional displays Computed tomography Two-dimensional displays Diffusion models Transformers Feature extraction Speech processing X-ray imaging image reconstruction Biomedical imaging

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ieee CIMSIVP 2011 committee symposium on computational intelligence for multimedia, signal and vision processing (ieee CIMSIVP 2011)

IEEE CIMSIVP 2011 committee symposium on computational intel...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

Constructive understanding of computational principles of multimedia, signal and visual information processing, perception and cognition is one of the most fundamental challenges of contemporary science. Deeper insight into such computational intelligence helps to advance intelligent systems research to achieve robust performance. Implementing integrated principles in artificial systems may help us achieve better, faster and more efficient intelligent systems. The symposium will address theory and applications of non-traditional computational intelligence approaches in multimedia, signal and vision processing.

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2009 ieee symposium computational intelligence for Multimedia signal and Vision processing, CIMSVP 2009 - Proceedings: Welcome Message

2009 IEEE Symposium Computational Intelligence for Multimedi...

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2009 ieee symposium computational intelligence for Multimedia signal and Vision processing, CIMSVP 2009 - Proceedings 2009年 V页

作者： Iftekharuddin, Khan M.

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Fourier approach to moving target indication and detection in multichannel SAR data

Fourier approach to moving target indication and detection i...

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ieee symposium on computational intelligence in image and signal processing

作者： Lidicky, Ludvik Delft Univ Technol IRCTR Delft Netherlands

ISBN: (纸本)9781424407071

This paper outlines a solution to the multi-channel synthetic aperture radar (SAR) moving target indication and detection (MTI/MTD) by means of inverse systems approach. A novel model of the problem is presented and an approximate analytic solution to it will be given. It will be demonstrated how a moving target indicator can benefit from a multichannel SAR system as opposed to a traditional approach that separates MTI and SAR systems. It will be shown that the problem of separation of moving targets from stationary ones can be solved completely by using multi-channel approach and in such a way that a spatial distribution of the stationary targets does not play a role.

关键词： Radar imaging Phased arrays Spaceborne radar Sensor arrays computational intelligence Radar detection Synthetic aperture radar Space technology Gold Radar signal processing

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Regularized High Temporal Resolution Fish Motion Synthesis

Regularized High Temporal Resolution Fish Motion Synthesis

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Tian, Jing Eng, How-Lung Inst Infocomm Res Singapore 138632 Singapore

ISBN: (纸本)9781467359177

This paper tackles the fish motion synthesis problem with the aim to increase the temporal resolution by generating a high frame rate video from a given video captured at a lower frame rate. The proposed approach reconstructs the virtual frames via estimating motion-vector fields that represent the correspondences between consecutive frames. To be more specific, the proposed approach utilizes two regularization functions: (i) an intra regularization function that is proposed to impose a local smoothness constraint on the estimated motion vector fields;and (ii) an inter regularization function that considers both intensity consistency and kinematic consistency between the reconstructed frame and its neighboring frames. Real-world fish motion video dataset is used to demonstrate the superior performance of the proposed approach in high temporal resolution fish motion synthesis, as well as its application in fish motion analysis.

关键词： image motion analysis image reconstruction image resolution video signal processing

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Identification of Mature Grape Bunches using image processing and computational intelligence Methods

Identification of Mature Grape Bunches using Image Processin...

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ieee symposium on computational intelligence for Multimedia, signal and Vision processing (CIMSIVP)

作者： Rahman, Ashfaqur Hellicar, Andrew CSIRO Autonomous Syst Program DP&S Hobart Tas Australia

ISBN: (纸本)9781479945030

Due to frost and insufficient exposure to sunlight, some grape bunches remain undeveloped during harvesting. For automation of harvesting, it is required to automatically identify the mature grape bunches. This paper presents a sequence of image processing and computational intelligence methods to identify mature grape bunches. It's a two-step process where in the first step the grape bunches are separated from the background of an image and in the second step the grape bunch is classified into mature and undeveloped group. We achieved 96.88% accuracy on the images obtained from a strip of vineyard in Cambridge, Tasmania.

关键词： Grape bunch detection yield estimation precision viticulture

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Minimum noiseless description length (MNDL) thresholding

Minimum noiseless description length (MNDL) thresholding

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ieee symposium on computational intelligence in image and signal processing

作者： Fakhrzadeh, Azadeh Beheshti, Soosan Ryerson Univ Dept Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)9781424407071

In this paper, a new thresholding approach for data denoising is presented. The approach is based minimum noiseless description length (MNDL), a new method for optimum sub-space selection in data representation. By using the observed noisy data, this information theoretic approach provides the optimum threshold that minimizes the description length of the noiseless signal. Comparison of the new method with the existing thresholding methods is provided.

关键词： Data processing

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A neural network based approach for the vehicle classification

A neural network based approach for the vehicle classificati...

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ieee symposium on computational intelligence in image and signal processing

作者： Goyal, Anshul Verma, Brijesh Univ Cent Queensland Rockhampton Qld 4702 Australia

ISBN: (纸本)9781424407071

This paper presents a neural network based approach for vehicle classification. The proposed vehicle classification approach extracts various features from a vehicle image, normalises and classifies them into one of the known classes. It is based on structural features and a direct solution training method. The preliminary experiments on training and testing of 4 types of vehicles patterns were conducted. The experimental results are very promising and demonstrate the effectiveness and usefulness of the proposed approach.

关键词： vehicle image classification neural networks pattern classification

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Measurements and computational intelligence in biomedical engineering

Measurements and computational intelligence in biomedical en...

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ieee International symposium on computational intelligence for Measurement Systems and Applications

作者： Micheli-Tzanakou, E Rutgers State Univ Dept Biomed Engn Piscataway NJ 08854 USA

ISBN: (纸本)0780377834

We have used advanced signal processing and innovative image processing methods that are used outside the operating room. The software is written in C++ in a windows environment and can be used on any PC. Applications will be discussed along with computational intelligence as used for diagnostic purposes and as visualization aids inside and outside the operating room. Subjects to be discussed, include blood cell classification, mammography, evoked potentials, ophthalmology, EEG and field potentials in Parkinson's disease. The latter methods along with 3D reconstruction of MRI images of Parkinson's patients, are currently used in the operating room for target assessment and electrode placement.

关键词： Application software Biomedical engineering Biomedical measurements Biomedical signal processing Blood Cells (biology) computational intelligence image processing Mammography Visualization

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