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检索条件"机构=Vision and Image Processing Laboratory with the Department of Systems"

共 458 条记录，以下是181-190 订阅

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Globally convergent 3D dynamic PET reconstruction with patch-based non-convex low rank regularization

Globally convergent 3D dynamic PET reconstruction with patch...

引用

IEEE International Symposium on Biomedical Imaging

作者： K. S. Kim Y. D. Son Z. H. Cho J. B. Ra J. C. Ye Bio Imaging & Signal Processing Laboratory Department of Bio& Brain Engineering Korea Advanced Institute of Science and Technology South Korea Neuroscience Research Institute Gachon University of Medicine and Science South Korea Image Systems Laboratory Electrical Engineering Korea Advanced Institute of Science and Technology South Korea

ISBN: (纸本)9781467364560

Dynamic positron emission tomography (PET) is widely used to measure variations of radiopharmaceuticals within the organs over time. However, conventional reconstruction algorithm can produce a noisy reconstruction if there are not sufficient photon counts. Hence, the main goal of this paper is to develop a novel spatio-temporal regularization approach that exploits inherent similarities within intra- and inter-frames to overcome the limitation. One of the main contributions of this paper is to demonstrate that such correlations can be exploited using a low rank constraint of overlapping similarity blocks. The resulting optimization framework is, however, non-smooth and non Lipschitz due to the low-rank penalty terms and Poisson log-likelihood. Therefore, we propose a novel globally convergent optimization method using the concave-convex procedure (CCCP) by exploiting Legendre-Fenchel transform, which overcomes the memory and computational limitations. We confirm that the proposed algorithm can provide significantly improved image quality and extract accurate kinetic parameters.

关键词： image reconstruction Positron emission tomography Heuristic algorithms Graphics processing units Minimization Optimization Biomedical imaging

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Haptic rendering of dense 3D point cloud data

Haptic rendering of dense 3D point cloud data

引用

2012 IEEE Haptics Symposium, HAPTICS 2012

作者： Sreeni, K.G. Chaudhuri, Subhasis Vision and Image Processing Laboratory Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai 400076 India

ISBN: (纸本)9781467308090

This work is aimed at rendering an object described by a dense point cloud data without a pre-computed polygonal mesh and surface normal information. We use a proxy based rendering technique with proxy collocated with the HIP in free space. To avoid sinking of proxy into the object during collision a sphere of sufficiently large radius is selected as the proxy so as to avoid it going through the point cloud. Once collision is detected, we minimize a cost function depending on the current HIP and proxy positions and find a new goal position for the proxy corresponding to the local minimum of the cost function. Our rendering algorithm continuously evaluates a tangential vector for the proxy to move over the object surface during collision. The penetration depth is calculated from the proxy to the HIP and is used to calculate the reaction force for the haptic device. We used our technique to render several dense point cloud based models. We also use the surface normal evaluated at the point of contact to shade the object surface when shown visually. © 2012 IEEE.

关键词： Cost functions

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Haptic rendering of variable density point cloud through local kernel bandwidth estimation 12

Haptic rendering of variable density point cloud through loc...

引用

8th Indian Conference on Computer vision, Graphics and image processing, ICVGIP 2012

作者： Sreeni, K.G. Chaudhuri, Subhasis Vision and Image Processing Laboratory Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai 400076 India

ISBN: (纸本)9781450316606

Haptic rendering of a point cloud data without a precomputed mesh structure is always a difficult problem. This paper tries to solve the problem of real time rendering a variable density 3D point cloud data as an optimization problem with a local kernel bandwidth estimation. In order to avoid the ambiguity of deciding the direction of reaction force while rendering the data we prefer a proxy based renderer. To avoid the proxy sinking into the object during collision the proxy point is always kept at minimum distance away from the object surface approximated by the point cloud. This minimum distance is computed during the rendering process depending on the local density of the points in the data using the kernel bandwidth estimation. Once collision is detected, we minimize a cost function depending on the current haptic interaction point (HIP) and proxy positions and find a new goal position for the proxy corresponding to the local minimum of the cost function. We validate the proposed technique by comparing the rendered force with the reaction force computed using a known spherical object. © 2012 ACM.

关键词： Cost functions

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REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE KERNEL-BASED EDGE ORIENTATION ESTIMATION AND TRUNCATED image RESTORATION

REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE ...

引用

IEEE International Conference on image processing

作者： Wonseok Kang Jaehwan Jeon Eunsung Lee Changhun Cho Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

This paper presents a novel real-time super-resolution (SR) method using directionally adaptive image interpolation and image restoration. The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation for reducing jagging artifacts in slanting edge regions. The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. Experimental results indicate that the proposed system gives higher peak-to-peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) values than the state-of-the-art image interpolation methods.

关键词： Super-resolution image interpolation image restoration digital zooming

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FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEFFICIENTS AND THEIR ADAPTIVE SHRINKAGE FOR ANTI-ALIASING

FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEF...

引用

IEEE International Conference on image processing

作者： Eunjung Chae Eunsung Lee Wonseok Kang Younghoon Lim Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

We present an antialiasing method using combined wavelet-Fourier transform and spatially adaptive shrinkage of the transform coefficients. Traditional antialiasing methods employ a simple low-pass filter onto the entire image, so the resulting image loses not only aliasing artifacts but also high-frequency components such as edges and ridges. The proposed algorithm analyzes the property of the LL subband of the discrete wavelet transform (DWT), and reduces aliasing artifacts using patch-adaptive shrinkage of the DWT coefficients. More specifically, an antialiased LL subband is obtained using adaptive patch-based aliasing reduction. To detect an aliased region, we subtract the discrete Fourier transform (DFT) coefficients of the LL subband from the DFT coefficients of antialiased LL subband. The detected aliasing artifacts in the LH, HL, and HH subbands are reduced by patch-wise adaptive shrinkage of the transform coefficients. The resulting antialiased image is obtained using the inverse DWT. The aliasing artifacts can be efficiently reduced by adaptively shrinking wavelet transform coefficients for preserving high-frequency image details. The proposed antialiasing algorithm is suitable for removing aliasing artifacts which frequently occur in imaging sensors with limited resolution.

关键词： Anti-aliasing wavelet-Fourier transform image enhancement patch-adaptive shrinkage antialiasing image enhancement Aliasing shrinkage Artifacts subband domain analysis Coefficients Sensors (image) Frequency-domain analysis discrete Fourier transform

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Realization of 2D Reverse-Lattice discrete filters

Realization of 2D Reverse-Lattice discrete filters

引用

5th International Symposium on Communications Control and Signal processing, ISCCSP 2012

作者： Antoniou, G.E. Department of Computer Science Image Processing and Systems Laboratory Montclair State University Montclair NJ 07043 United States

ISBN: (纸本)9781467302760

In this paper state space and circuit realizations are presented for 2D Reverse-Lattice based filters. The proposed state space realizations are based on the corresponding circuit implementation. For the state space realization the 2D Cyclic model, having minimal dimension and delay elements, is used. Two low-order representative examples are presented to illustrate the proposed results using, 2D all-pass and all-pole with a scale factor, realization structures. © 2012 IEEE.

关键词： Timing circuits

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What can an image of a smooth Lambertian surface tell about camera nonlinearity?

What can an image of a smooth Lambertian surface tell about ...

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2012 9th Conference on Computer and Robot vision, CRV 2012

作者： El-Melegy, Moumen T. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9780769546834

This paper investigates the use of a single image of a smooth Lambertian surface to calibrate and remove some image nonlinearities due to the imaging device. To the best of our knowledge, this has not been addressed before in the literature. We show that this is possible, both theoretically and practically, taking advantage of some local shading measures that vary nonlinearly as a function of luminance and geometric nonlinearities (e.g., gamma correction and lens distortion). This can work as a basis for developing a simple method to estimate these nonlinearities from a single image. Several experiments are reported to validate the proposed method. © 2012 IEEE.

关键词： Cameras

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Heat kernels for non-rigid shape retrieval: Sparse representation and efficient classification

Heat kernels for non-rigid shape retrieval: Sparse represent...

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2012 9th Conference on Computer and Robot vision, CRV 2012

作者： Abdelrahman, Mostafa El-Melegy, Moumen Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9780769546834

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Lap lace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem. © 2012 IEEE.

关键词： Computer vision

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Regularized Gradient Kernel Anisotropic Diffusion for Better image Filtering

Regularized Gradient Kernel Anisotropic Diffusion for Better...

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Canadian Conference on Computer and Robot vision, CRV

作者： Amir H. Shabani John S. Zelek David A. Clausi Vision and Image Processing Laboratory Intelligent Systems Laboratory University of Waterloo ONT Canada Intelligent Systems Laboratory University of Waterloo ONT Canada Vision and Image Processing Laboratory University of Waterloo ONT Canada

This paper proposes an extension to anisotropic diffusion filtering for a better preservation of semantically meaningful structures such as edges in an image in its smoothing/denoising process. The problem of separation of the gradients due to edges and the gradients due to noise is formulated as a nonlinearly separable classification problem. More specifically, the spatially-regularized image gradient is mapped to a higher dimensional Reproducing Kernel Hilbert Space (RKHS) in which the gradients of the edges from those of noise can be readily separated. This proper discrimination of edges prevents the filter from blurring the edges, while smoothing the image. Compared to the existing anisotropic filters, the proposed method improves the denoising and smoothing of an image on both synthetic and real images.

关键词： image edge detection Anisotropic magnetoresistance Kernel Smoothing methods Noise Noise reduction Design automation

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Evaluation of Local Spatio-temporal Salient Feature Detectors for Human Action Recognition

Evaluation of Local Spatio-temporal Salient Feature Detector...

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Canadian Conference on Computer and Robot vision, CRV

作者： Amir H. Shabani David A. Clausi John S. Zelek Vision and Image Processing Laboratory Intelligent Systems Laboratory University of Waterloo ONT Canada Vision and Image Processing Laboratory University of Waterloo ONT Canada Intelligent Systems Laboratory University of Waterloo ONT Canada

Local spatio-temporal salient features are used for a sparse and compact representation of video contents in many computer vision tasks such as human action recognition. To localize these features (i.e., key point detection), existing methods perform either symmetric or asymmetric multi-resolution temporal filtering and use a structural or a motion saliency criteria. In a common discriminative framework for action classification, different saliency criteria of the structured-based detectors and different temporal filters of the motion-based detectors are compared. We have two main observations. (1) The motion-based detectors localize features which are more effective than those of structured-based detectors. (2) The salient motion features detected using an asymmetric temporal filtering performbetter than all other sparse salient detectors and dense sampling. Based on these two observations, we recommend the use of asymmetric motion features for effective sparse video content representation and action recognition.

关键词： Feature extraction Detectors Humans Training Cameras Standards Accuracy

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