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17th International conference on Computer Graphics and vision, GraphiCon 2007

作者： Nasonov, Andrey Krylov, Andrey S. Lukin, Alexey Moscow State University Moscow Russia

image restoration is one of classical inverse problems in image processing and computer vision, which consists of the recovering information about the original image from incomplete or degraded data. In this paper, we consider the problem of reduction of ringing that appears after image resampling. We introduce a novel method for image restoration, based on a quasi-solution method for a compact set of functions with bounded total variation. It is an alternative approach to using a total variation functional as a stabilizer in Tikhonov regularization, and it does not oversmooth or displace edges.

关键词： image reconstruction

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IEEE International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Guha, Tanaya Ward, Rabab K. Aboulnasr, Tyseer Univ British Columbia Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781479903566

This paper presents a new approach to measuring the similarity between two images using sparse reconstruction. Our approach alleviates the difficulty of selecting and extracting suitable features from images which usually requires domain-specific knowledge. The proposed measure, the Sparse SNR (SSNR), does not use any prior knowledge about the data type or the application. SSNR is generic in the sense that it is applicable, without modification, to a variety of problems involving different types of images. Given a pair of images, a set of basis vectors (dictionary) is learnt for each image such that each image can be represented as a linear combination of a small number of its dictionary elements. Each image is reconstructed by two dictionaries - the one trained on the image itself and the second - trained on the other image. We develop a novel similarity measure based on the resulting reconstruction errors. To the best of our knowledge, this is the first attempt to develop a sparse reconstruction-based similarity measure. Excellent classification, clustering and retrieval results are achieved on benchmark datasets involving facial images and textures.

关键词： image similarity overcomplete dictionary sparse reconstruction

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image reconstruction using bistable gradient neural-like networks

Image reconstruction using bistable gradient neural-like net...

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International Joint conference on Neural Networks (IJCNN 01)

作者： Chinarov, v Menzinger, M Univ Toronto Dept Chem Toronto ON M5S 1A1 Canada

ISBN: (纸本)0780370449

We present a novel bistable gradient neural-like network (BGN) and demonstrate its potential applications for image processing where data are corrupted by high intensity additive or multiplicative noise, or both. The goal is to develop an adaptive computational network that incorporates the physics of many-body interactions and operational rules of biological systems. We apply BGN to restore unknown images, which have been degraded by random blurring matrix and additive Gaussian white noise. The competitive advantage of BGN derives from its: nice generalization capabilities, existence of the unique attractor with the lowest energy that is worked out when several patterns are stored by the network, and fast guaranteed convergence to this attractor.

关键词： image reconstruction

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image reconstruction using em method in X-ray CT

Image reconstruction using em method in X-ray CT

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5th International conference on Wavelet Analysis and Pattern Recognition

作者： Dong, Bao-Yu Dalian Jiaotong Univ Sch Elect & Informat Dalian 116028 Peoples R China

ISBN: (纸本)9781424410651

Computed tomography (CT) is a technique for imaging cross-sections of an object using a series of X-ray Measurements taken from different angles around the object. It has been widely applied in diagnostic medicine and industrial non-destructive testing. Traditional CT reconstructions are limited by many kinds of artifacts, and they give dissatisfactory image. To reduce image noise and artifacts, the theory of maximum likelihood estimation is extended to v-ray scan in this paper, and expectation maximization (EM) algorithm is studied and implemented for image reconstruction of X-ray CT (XCT). Then the point spread function and modulation transfer function of the EM algorithm is analyzed. Last experimental results with computer simulated data and real CT data are presented to verify our method is effective.

关键词： EM algorithin maximum likelihood estimation image reconstruction X-ray CT

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Sensor Saturation in Fourier Multiplexed Imaging

Sensor Saturation in Fourier Multiplexed Imaging

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23rd IEEE conference on Computer vision and Pattern Recognition (CvPR)

作者： Wetzstein, Gordon Ihrke, Ivo Heidrich, Wolfgang Univ British Columbia Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781424469840

Optically multiplexed image acquisition techniques have become increasingly popular for encoding different exposures, color channels, light fields, and other properties of light onto two-dimensional image sensors. Recently, Fourier-based multiplexing and reconstruction approaches have been introduced in order to achieve a superior light transmission of the employed modulators and better signal-to-noise characteristics of the reconstructed data. We show in this paper that Fourier-based reconstruction approaches suffer from severe artifacts in the case of sensor saturation, i.e. when the dynamic range of the scene exceeds the capabilities of the image sensor. We analyze the problem, and propose a novel combined optical light modulation and computational reconstruction method that not only suppresses such artifacts, but also allows us to recover a wider dynamic range than existing image-space multiplexing approaches.

关键词： image sensors

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Iterative reconstruction of large scenes using heterogeneous feature tracking

Iterative reconstruction of large scenes using heterogeneous...

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26th IEEE conference on Computer vision and Pattern Recognition (CvPR)

作者： Rohith, M., v Rhein, Stephen Lu, Guoyu Sorensen, Scott Mahoney, Andrew R. Eicken, Hajo Ray, G. Carleton Kambhamettu, Chandra Univ Delaware Dept Comp & Informat Sci Video Image Modeling & Synth VIMS Lab Delaware OH 43015 USA Univ Alaska Fairbanks Inst Geophys Fairbanks AK 99709 USA Univ Virginia Dept Environm Sci Charlottesville VA 22903 USA

ISBN: (纸本)9780769549903

With image capturing technology growing ubiquitous in consumer products and scientific studies, there is a corresponding growth in the applications that utilize scene structure for deriving information. This trend has also been reflected in the plethora of recent studies on reconstruction using robust structure from motion, bundle adjustment, and related techniques. Most of these studies, however, have concentrated on unstructured collections of images. In this paper, we propose a feature tracking and reconstruction framework for structured image collections using heterogenous features. This is motivated by the observation that images contain a small number of features that are fast/easy to track and a large number of features that are difficult/slow to track. By tracking these separately, we show that we can not only improve the tracking speed, but also improve the tracking accuracy by using a camera geometry based descriptor. We demonstrate this on a new challenging dataset which contains images of Arctic sea ice. The reconstruction pipeline constructed using the proposed method provides near real time reconstruction of the scene, enabling the user to parse vast amounts of data rapidly. Quantitative comparisons with baseline SFM techniques show that reconstruction accuracy does not suffer.

关键词： computational geometry feature extraction geophysical image processing image motion analysis image reconstruction image sensors iterative methods object tracking sea ice

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Towards Multi-Modal image-Guided Tumour Identification in Robot-Assisted Partial Nephrectomy

Towards Multi-Modal Image-Guided Tumour Identification in Ro...

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2nd Middle East conference on Biomedical Engineering (MECBME)

作者： Hamarneh, Ghassan Amir-Khalili, Alborz Nosrati, Masoud S. Figueroa, Ivan Kawahara, Jeremy Al-Alao, Osama Peyrat, Jean-Marc Abi-Nahed, Julien Al-Ansari, Abdulla Abugharbieh, Rafeef Simon Fraser Univ Med Image Anal Lab Burnaby BC V5A 1S6 Canada Univ British Columbia Biomed Signal & Image Comp Lab Vancouver BC V5Z 1M9 Canada Qatar Robot Surg Ctr Doha Qatar Hamad Med Corp Dept Urol Doha Qatar

ISBN: (纸本)9781479947997

Tumour identification is a critical step in robotassisted partial nephrectomy (RAPN) during which the surgeon determines the tumour localization and resection margins. To help the surgeon in achieving this step, our research work aims at leveraging both pre- and intra-operative imaging modalities (CT, MRI, laparoscopic US, stereo endoscopic video) to provide an augmented reality view of kidney-tumour boundaries with uncertainty-encoded information. We present herein the progress of this research work including segmentation of preoperative scans, biomechanical simulation of deformations, stereo surface reconstruction from stereo endoscopic camera, pre-operative to intra-operative data registration, and augmented reality visualization.

关键词： augmented reality biomechanics biomedical MRI biomedical optical imaging computerised tomography deformation endoscopes image reconstruction image registration image segmentation kidney medical image processing medical robotics stereo image processing surgery tumours CT MRI augmented reality visualization biomechanical simulation computed tomography deformations intraoperative data registration kidney-tumour boundaries laparoscopic US magnetic resonance imaging multimodal image-guided tumour identification preoperative data registration preoperative scan segmentation robot-assisted partial nephrectomy stereo endoscopic camera stereo endoscopic video stereo surface reconstruction uncertainty-encoded information Biological system modeling Computed tomography Kidney Stereo image processing Surface reconstruction Surgery Tumors

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Depth Camera Based Fluid reconstruction and its Solid-fluid Interaction 19

Depth Camera Based Fluid Reconstruction and its Solid-fluid ...

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32nd International conference on Computer Animation and Social Agents (CASA)

作者： Feng, Xiaobing Zhang, Juan Zhu, Dengming Shi, Min Wang, Zhaoqi Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Chinese Acad Sci Virtual Real Lab Inst Comp Technol Beijing Peoples R China North China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China

ISBN: (纸本)9781450371599

Fluid animation has great value in study and application in many fields, such as video special effects, virtual reality and so on. However, due to the complexity and irregularity of fluid's motion, the existing simulation methods cannot make a good tradeoff between computational efficiency and realism. In this paper, a method of fluid animation synthesis based on depth camera is proposed. The RGB-D (red, green, blue-depth) data, captured by a RealSense camera, are used to reconstruct the fluid surface. By analysis the relation between color intensity and height field gradient of water surface, we use the RGB image as guidance to denoise the depth image, then possion reconstruction is employed to repair the incomplete data of depth image and fuse detail feature from the RGB to the reconstruction fluid surface. In addition, we propose a real-time method to simulate the interaction between solid and fluid, which is implemented on the wave particle system that fitted to the reconstruction fluid surface. Experiments show that the presented method can reconstruct fluid effectively and generate fluid animation of solid-fluid interaction plausibly.

关键词： data-driven depth camera fluid reconstruction fluid-solid interaction particles

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Performance-based assessment of reconstructed images

Performance-based assessment of reconstructed images

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conference on Medical Imaging - image Perception, Observer Performance, and Technology Assessment

作者： Hanson, Kenneth M. Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)9780819475145

During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that the quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default "classic" value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.

关键词： tomographic reconstruction assessment of image quality Rayleigh discrimination task ROC analysis human observer machine observer entropic prior ART reconstruction algorithm MEMSYS Robert Wagner

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virtual reality and Web tools to convey the visual information of ancient monuments

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COMPUTER NETWORKS AND ISDN SYSTEMS 1997年第14期29卷 1655-1660页

作者： Marini, D Rossi, M Moltedo, L Salvetti, O IAC CNR I-00161 ROMEITALY IEI CNR I-56126 PISAITALY

visual communication and visual knowledge are areas that can take important benefits from mature CG technologies. This paper demonstrates a methodology to give new insights into cultural heritage which is based on virtual reality techniques, Web navigation tools, advanced image analysis and photorealistic image synthesis methods. A vRML model of the ancient Roman Theatre of Aosta is the basis to explore multiple data types describing the current status of the building and to examine possible restoration and conservation choices. JAvA scripts increase the degree of interactivity with the data collected by the experts. Photometric and colorimetric data are derived by analysing stones. image analysis and surface reconstruction algorithms are used to obtain a geometric representation of stones, necessary to produce photorealistic samples of both the present status and the past and future conditions of the building. The final rendering, using vRML tools, has been implemented by adopting texturing as well as photorealistic methods. (C) 1997 Elsevier Science B.v.

关键词： image analysis photorealistic images virtual reality Web tools cultural heritage

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