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Earth Remote Sensing Using the Landsat Thermatic Mapper and SPOT Sensor Systems 1986

作者： Banninger, C. Institute for Image Processing and Computer Graphics Research Centre Joanneum Graz Austria

Spring and summer acquired Thematic Mapper data of a spruce forest growing in southeastern Austria show the normalised differences ND1 and ND3, ratio R41, band differences BD1 and BD3, and the greenness index TMG employing Thematic Mapper bands 1, 3, and 4 best discriminate copper-lead-zinc stress in spruce trees of thirty Thematic Mapper single bands and transformations examined. Stress detection is slightly better in the summer versus the spring scene data. © 1986 SPIE. All rights reserved.

关键词： Remote sensing

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Stereo-viewing from space

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Advances in Space research 1989年第1期9卷 29-40页

作者： Buchroithner, M.F. Institute for Image Processing and Computer Graphics Graz Research Center A-8010 Graz Wastiangasse 6 Austria

Spaceborne stereo-imagery can serve two major purposes: relief mapping and extraction of thematic information. Not only camera-acquired photogrammetric data of conventional and super-large format, but also hand-held photographs can be used. In addition, satellite scanner and spaceborne radar data are also available for stereo-evaluation using analytical plotting devices. For topographic as well as for thematic mapping, stereopsis offers an additional dimension of image information. Mapping of geomorphological features, which, for example, represent indicators of geological processes, is hardly feasible in monoscopic mode. Examples of three-dimensional and thematic stereo-evaluation are given for image data of the following sensors: Spacelab Metric Camera, Large Format Camera, Space Shuttle Hand-Held Hasselblad Camera, Landsat Thematic Mapper, SPOT High Resolution Visible Instrument, Shuttle Imaging Radar (SIR) A and B. Accuracies achievable under more or less operational conditions for the mapping procedure are discussed. © 1989.

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Cone-Beam Computed Tomography Limited-Angle image Reconstruction Using Planning CT-Guided Deep Diffusion Model

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Wu, Zhan Yang, Yang Hu, Dianlin Lyu, Tianling Li, Yinsheng Tang, Hao Shu, Huazhong Xi, Yan Zhang, Yi Chen, Yang Southeast University Laboratory of Image Science and Technology Nanjing 210096 China Southeast University Ministry of Education Key Laboratory of Computer Network and Information Integration Nanjing 210096 China Zhejiang University of Technology Academy for Advanced Interdisciplinary Science and Technology Hangzhou China Chinese Academy of Sciences Key Laboratory of Biomedical Imaging Science and System China Capital Medical University Beijing Jishuitan Hospital China First-Imaging Tech Shanghai China Sichuan University School of Cyber Science and Engineering Chengdu China Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Laboratory of Image Science and Technology the School of Computer Science and Engineering Nanjing 210096 China

For existing image-guided radiation therapy systems (IGRT), the limited angular range of the cone-beam computed tomography (CBCT) scanning improves the compactness of the system and compatibility between CBCT and linear accelerator configurations. However, the limited-angle CBCT reconstruction under incomplete projection data causes severe artifacts in the reconstructed images, further having a negative impact on the registration accuracy in IGRT. In this paper, we propose a planning CT-guided deep diffusion model, termed LARGE-DiffNet, to improve imaging quality and registration accuracy for limited-angle CBCT image reconstruction. In stark contrast to existing approaches leveraging hand-crafted regularization, such as local smoothness and/or sparsity of the image, LARGE-DiffNet learns the distribution-level prior knowledge to describe the features of ideal CBCT images via a planning CT-guided diffusion model. The proposed LARGE-DiffNet is evaluated on the clinical CBCT dataset, and extensive experimental results demonstrate that the proposed method outperforms the state-of-the-art methods. The proposed LARGE-DiffNet technique has great potential in IGRT. © 1963-2012 IEEE.

关键词： cone-beam computed tomography deep learning diffusion model image registration image-guided radiation therapy limited-angle

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Multi-Scale Cascaded with Cross-Attention Network-Based Deformation Vector Field Estimation for Motion-Compensated 4D-CBCT Reconstruction

IEEE Transactions on Computational Imaging

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IEEE Transactions on Computational Imaging 2025年 11卷 717-731页

作者： Yuan, Peng Lyu, Fei Gao, Zhiqiang Yang, Chunfeng Hu, Dianlin Zhu, Jian Wu, Zhan Lyu, Tianling Zhao, Wei Dong, Jianmin Chen, Yang Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Ministry of Education Southeast University Nanjing210096 China Laboratory of Image Science and Technology Southeast University Nanjing210096 China Department of Computer Science Hong Kong Baptist University Hong Kong Hong Kong Academy for Advanced Interdisciplinary Science and Technology Zhejiang University of Technology Hangzhou China School of Physics Beihang University Beijing China Beihang Hangzhou Innovation Institute Zhejiang Hangzhou China School of Shandong Cancer Hospital and Institute Shandong First Medical University Shandong Academy of Medical Sciences Jinan Shandong China School of Information Engineering Xizang Minzu University Xianyang712082 China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Laboratory of Image Science and Technology The School of Computer Science and Engineering Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Nanjing210096 China

Four-Dimensional Cone Beam Computed Tomography (4D-CBCT) imaging technology offers enhanced image quality and spatial resolution for intraoperative guidance, facilitating real-time tracking of tumor position changes during radiotherapy. However, this is still a task of great challenges due to insufficient projections at each respiratory phase after phase-sorting, and the image phases reconstructed directly from phase-sorted data are discrete and discontinuous. To generate high-quality 4D-CBCT deformation vector fields (DVFs), this paper leverages the preoperative static prior image to guide intraoperative dynamic sparse-view reconstruction images for reducing anatomical structure differences, ultimately achieving continuous and dynamic 4D-CBCT imaging. In this paper, we propose a Multi-scale Cascaded residual deformable vector field estimation framework based on Cross-attention in Motioncompensated 4D-CBCT reconstruction (MCCM), which combines Multi-Scale Cascaded residual registration network (MSCNet), Cross-Attention Enhanced feature Fusion (CAEF) module and Structure-Enhanced Motion-Compensated (SEMC) module: 1) the MCCM employs a multi-scale cascaded residual network strategy, merging multi-receptive fields and multi-resolution feature maps for large-scale internal changes. 2) the CAEF is embedded into MSC-Net to facilitate effective communication and learning between features and promote the flow of information. 3) the SEMC is developed to reduce artifacts after intraoperative CBCT sparse-view reconstruction, restore global lung motion changes and local details, and enhance structural information through image fusion. The proposed method has been evaluated using simulated and clinical datasets and has shown promising results by comparative experiment. Our approach exhibits significant improvements across various evaluation metrics. © 2024 IEEE.

关键词： image fusion

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New method in information processing for maintaining an efficient dynamic ordered set

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Science in China(Series F) 2009年第8期52卷 1292-1301页

作者： XIN ShiQing WANG GuoJin Institute of Computer Graphics and Image Processing Zhejiang University Hangzhou 310027 China State Key Laboratory of CAD & CG Zhejiang University Hangzhou 310027 China

This paper investigates how to maintain an efficient dynamic ordered set of bit strings, which is an important problem in the field of information search and information processing. Generally, a dynamic ordered set is required to support 5 essential operations including search, insertion, deletion, max-value retrieval and next-larger-value retrieval. Based on previous research fruits, we present an advanced data structure named rich binary tree （RBT）, which follows both the binary-search-tree property and the digital-search-tree property. Also, every key K keeps the most significant difference bit （MSDB） between itself and the next larger value among K＇s ancestors, as well as that between itself and the next smaller one among its ancestors. With the new data structure, we can maintain a dynamic ordered set in O（L） time. Since computers represent objects in binary mode, our method has a big potential in application. In fact, RBT can be viewed as a general-purpose data structure for problems concerning order, such as search, sorting and maintaining a priority queue. For example, when RBT is applied in sorting, we get a linear-time algorithm with regard to the key number and its performance is far better than quick-sort. What is more powerful than quick-sort is that RBT supports constant-time dynamic insertion/deletion.

关键词： information processing dynamic ordered set algorithms and data structures rich binary tree

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Recognition of areal features for map-guided image analysis

Recognition of areal features for map-guided image analysis

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Applications of Digital image processing V 1983

作者： Ranzinger, Hubert Kropatsch, Walter Institute for Image Processing and Computer Graphics Research Centre Wastiangasse 6 Graz8010 Austria

The analysis of images can take advantage of existing knowledge;this may be denoted as data-driven or knowledge-based image analysis. One example is the use of topographic maps in the study of aerial imagery. We report on a software system for object recognition using map-guidance. Three algorithms have been developed to find areally extended objects in a digital image. Results can be applied to compare a map data base with an image;to monitor changes;to geometric and radiometric rectification;to support classification with training areas and other tasks. © 1983 Proceedings of SPIE - The International Society for Optical Engineering.

关键词： image analysis

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Three-dimensional image analysis and display by space-scale matching of cross sections

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Journal of the Optical Society of America A: Optics and image Science, and Vision 1989年第6期6卷 890-899页

作者： Algazi, V.R. Reutter, B.W. van Warmerdam, W.L.G. Liu, C.C. Graphics Image and Vision Engineering Research Laboratory Center for Image Processing and Integrated Computing University of California Davis CA 95616 United States

We present a framework and a set of techniques for the analysis and display of three-dimensional experimental data or images. We assume that the data are available in the form of two-dimensional cross sections of the three dimensional data set. We describe our approach, which has for goals to extract significant information from the three-dimensional data set and to display this information as objects that can be manipulated in three-dimensional space. The high-contrast transitions of two-dimensional cross sections are extracted first;they define a set of contours to be matched from cross section to cross section. This matching is performed by space-scale analysis of the orientation of contours on adjacent cross sections. By modeling the contours as B splines, we then make use of three-dimensional B-spline patches to generate significant surfaces that can be displayed, rendered, and rotated with standard computer graphics techniques and specialized processors. © 1989 Optical Society of America.

关键词： Computed tomography computer simulation image analysis image processing Imaging systems Three dimensional imaging

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Interactive simulation and visualization of fluids with surface raycasting

Interactive simulation and visualization of fluids with surf...

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23rd SIBGRAPI Conference on graphics, Patterns and images, SIBGRAPI 2010

作者： Inácio, Renan Teston Nobrega, Tiago H. C. Carvalho, Diego D. B. Von Wangenheim, Aldo LAPIX - Laboratory for Image Processing and Computer Graphics Federal University of Santa Catarina Florianópolis Brazil

ISBN: (纸本)9780769542300

We present a method to couple particle-based fluid simulation methods such as Smoothed Particle Hydrodynamics (SPH) and volume rendering in order to visualize the fluid. A volume is generated from the fluid's implicit density field so volume raycasting can be performed to render the surface on the GPU. The volume generation algorithm is also implemented in the GPU and is suitable to be used with both SPH simulations implemented on CPU and GPU. We compare different implementations of fluid simulation, demonstrating the modularity of the volume generation method and concluding that it can be used together with other particle-based simulation models and other volume rendering techniques. © 2010 IEEE.

关键词： graphics processing unit

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EFFICIENT CLASSIFICATION FOR LARGE-SCALE PROBLEMS BY MULTIPLE LDA SUBSPACES

EFFICIENT CLASSIFICATION FOR LARGE-SCALE PROBLEMS BY MULTIPL...

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4th International Conference on computer Vision Theory and Applications

作者： Uray, Martina Roth, Peter M. Bischof, Horst Institute of Digital Image Processing Joanneum Research Austria Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9789898111692

In this paper we consider the limitations of Linear Discriminative Analysis (LDA) when applying it for large-scale problems. Since LDA was originally developed for two-class problems the obtained transformation is sub-optimal if multiple classes are considered. In fact, the separability between the classes is reduced, which decreases the classification power. To overcome this problem several approaches including weighting strategies and mixture models were proposed. But these approaches are complex and computational expensive. Moreover, they were only tested for a small number of classes. In contrast, our approach allows to handle a huge number of classes showing excellent classification performance at low computational costs. The main idea is to split the original data into multiple sub-sets and to compute a single LDA space for each sub-set. Thus, the separability in the obtained subspaces is increased and the overall classification power is improved. Moreover, since smaller matrices have to be handled the computational complexity is reduced for both, training and classification. These benefits are demonstrated on different publicly available datasets. In particular, we consider the task of object recognition, where we can handle up to 1000 classes.

关键词： LDA image classification Large databases

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Degree elevation operator and geometric construction of C-B-spline curves

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Science China(Information Sciences) 2010年第9期53卷 1753-1764页

作者： ZHU Ping1,2*,WANG GuoZhao1 & YU JingJing1 1Institute of computer graphics and image processing,Zhejiang University,Hangzhou 310027,China 2laboratory of Scientific Computing,Southeast University,Nanjing 211189,China 1. Institute of Computer Graphics and Image Processing Zhejiang University Hangzhou 310027 China2. Laboratory of Scientific Computing Southeast University Nanjing 211189 China

Unlike a B'ezier curve,a spline curve is hard to be obtained through geometric corner cutting on control polygons because the degree elevation operator is difficult to be obtained and geometric convergence is hard to be *** order to obtain geometric construction algorithm on C-B-splines,firstly we construct the degree elevation operator by using bi-order splines in this *** we can obtain a control polygon sequence by degree elevation based on the degree elevation operator derived from a C-B-spline ***,we prove that this polygon sequence will converge to initial C-B-spline *** geometric construction algorithm possesses strong geometric *** is also simple,stable and suitable for hardware to *** algorithm is important for CAD modeling systems,since many common engineering curves such as ellipse,helix,*** be represented explicitly by C-B-splines.

关键词： C-B-spline degree elevation operator bi-order C-B-spline geometric convergence geometric construction

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