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Single frame image super-resolution: should we process locally or globally?

MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2007年第2-3期18卷 123-152页

作者： Jiji, C. v. Chaudhuri, Subhasis Chatterjee, Priyam Indian Inst Technol Dept Elect Engn Bombay 400076 Maharashtra India

In this paper we study the usefulness of different local and global, learning-based, single-frame image super-resolution reconstruction techniques in handling three specific tasks, namely, de-blurring, de-noising and alias removal. We start with the global, iterative Papoulis-Gerchberg method for super-resolving a scene. Next we describe a PCA-based global method which faithfully reproduces a super-resolved image from a blurred and noisy low resolution input. We also study several multi-resolution processing schemes for super-resolution where the best edges are learned locally from an image database. We show that the PCA-based global method is efficient in handling blur and noise in the data. The local methods are adept in capturing the edges properly. However, both local and global approaches cannot properly handle the aliasing present in the low resolution observation. Hence we propose an alias removal technique by designing an alias-free upsampling scheme. Here the unknown high frequency components of the given partially aliased (low resolution) image is generated by minimizing the total variation of the interpolant subject to the constraint that part of alias free spectral components in the low resolution observation are known precisely and under the assumption of sparsity in the data.

关键词： super-resolution principal components wavelet contourlet decomposition filter banks edge primitives image interpolation aliasing

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Compressed Sensing image reconstruction via Recursive Spatially Adaptive Filtering

Compressed Sensing Image Reconstruction Via Recursive Spatia...

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IEEE International conference on image Processing

作者： Karen Egiazarian Alessandro Foi vladimir Katkovnik Institute of Signal Processing Tampere University of Technology Tampere Finland

We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coefficients of an arbitrary linear transform. This reconstruction problem is the subject of intensive study in the recent field of "compressed sensing" (also known as "compressive sampling"). Our approach is based on a quite specific recursive filtering procedure. At every iteration the algorithm is excited by injection of random noise in the unobserved portion of the spectrum and a spatially adaptive image denoising filter, working in the image domain, is exploited to attenuate the noise and reveal new features and details out of the incomplete and degraded observations. This recursive algorithm can be interpreted as a special type of the Robbins-Monro stochastic approximation procedure with regularization enabled by a spatially adaptive filter. Overall, we replace the conventional parametric modeling used in CS by a nonparametric one. We illustrate the effectiveness of the proposed approach for two important inverse problems from computerized tomography: Radon inversion from sparse projections and limited-angle tomography. In particular we show that the algorithm allows to achieve exact reconstruction of synthetic phantom data even from a very small number projections. The accuracy of our reconstruction is in line with the best results in the compressed sensing field.

关键词： Compressed sensing image reconstruction Adaptive filters image coding image sampling Filtering image denoising Degradation Approximation algorithms Stochastic resonance

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Single frame image super-resolution: should we process locally or globally?

Single frame image super-resolution: should we process local...

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International conference on Superresolution Imaging

作者： Jiji, C. v. Chaudhuri, Subhasis Chatterjee, Priyam Indian Inst Technol Dept Elect Engn Bombay 400076 Maharashtra India

关键词： super-resolution principal components wavelet contourlet decomposition filter banks edge primitives image interpolation aliasing

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Hybrid Scene reconstruction by Integrating Scan data and Stereo image Pairs

Hybrid Scene Reconstruction by Integrating Scan Data and Ste...

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International conference on 3D Imaging, Modeling, Processing, visualization and Transmission (3DIMPvT)

作者： Xiangyin Ma Hongbin Zha State Key Laboratory of Machine Perception Peking University Beijing China

3D geometric models obtained by using laser scanners are often incomplete due to the equipment limitations. In this paper, we propose a novel hybrid reconstruction algorithm, which integrates stereo image pairs to overcome these limitations. This work focuses on a category of scenes that can be approximated by planes (such as manmade scenes). The scan data are first segmented into planar patches, many of which may be incomplete. Stereo image pairs are then incorporated to retrieve the missing data. Specifically, we decide each plane's extension in the image domain via segment-based stereo matching with disparity layers extracted from scan data. Then, points in the missing area are interpolated by calculating ray-plane intersections. All procedures are automatic except for the range to image registration. The validity of our approach is demonstrated by experiments on real data.

关键词： Layout image reconstruction Stereo image processing image segmentation Solid modeling Laser modes reconstruction algorithms Information retrieval image retrieval data mining

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Simultaneous covariance driven correspondence (CDC) and transformation estimation in the expectation maximization framework

Simultaneous covariance driven correspondence (CDC) and tran...

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IEEE conference on Computer vision and Pattern Recognition

作者： Sofka, Michal Yang, Gehua Stewart, Charles v. Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA

ISBN: (纸本)9781424411795

This paper proposes a new registration algorithm, Covariance Driven Correspondences (CDC), that depends fundamentally on the estimation of uncertainty in point correspondences. This uncertainty is derived from the covariance matrices of the individual point locations and from the covariance matrix of the estimated transformation parameters. Based on this uncertainty, CDC uses a robust objective function and an EM-like algorithm to simultaneously estimate the transformation parameters, their covariance matrix, and the likely correspondences. Unlike the Robust Point Matching (RPM) algorithm, CDC requires neither an annealing schedule nor an explicit outlier process. Experiments on synthetic and real images using a polynomial transformation models in 2D and in 3D show that CDC has a broader domain of convergence than the well-known Iterative Closest Point (ICP) algorithm and is more robust to missing or extraneous structures in the data than RPM.

关键词： image reconstruction

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Faithful recovery of vector valued functions from incomplete data recolorization and art restoration

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1st International conference on Scale Space and variational Methods in Computer vision, SSvM 2007

作者： Fornasier, Massimo Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 United States

ISBN: (纸本)9783540728221

On March 11, 1944, the famous Eremitani Church in Padua (Italy) was destroyed in an Allied bombing along with the inestimable frescoes by Andrea Mantegna et al. contained in the Ovetari Chapel. In the last 60 years, several attempts have been made to restore the fresco fragments by traditional methods, but without much success. We have developed an efficient pattern recognition algorithm to map the original position and orientation of the fragments, based on comparisons with an old gray level image of the fresco prior to the damage. This innovative technique allowed for the partial reconstruction of the frescoes. Unfortunately, the surface covered by the fragments is only 77 m 2, while the original area was of several hundreds. This means that we can reconstruct only a fraction (less than 8%) of this inestimable artwork. In particular the original color of the blanks is not known. This begs the question of whether it is possible to estimate mathematically the original colors of the frescoes by making use of the potential information given by the available fragments and the gray level of the pictures taken before the damage. Can one estimate how faithful such restoration is? In this paper we retrace the development of the recovery of the frescoes as an inspiring and challenging real-life problem for the development of new mathematical methods. We introduce two models for the recovery of vector valued functions from incomplete data, with applications to the fresco recolorization problem. The models are based on the minimization of a functional which is formed by the discrepancy with respect to the data and additional regularization constraints. The latter refer to joint sparsity measures with respect to frame expansions for the first functional and functional total variation for the second. We establish the relations between these two models. As a byproduct we develop the basis of a theory of fidelity in color recovery, which is a crucial issue in art restoration and

关键词： vectors

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image-based Model Completion

Image-based Model Completion

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International conference on 3D Imaging, Modeling, Processing, visualization and Transmission (3DIMPvT)

作者： Alan Brunton Stefanie Wuhrer Chang Shu Visual Information Technology Group National Research Council Canada Ottawa Canada School of Computer Science Carleton University Canada

Geometric models created from range sensors are usually incomplete. Considerable effort has been made to fix this problem, ranging from manual repairing to geometric interpolation. We propose using multi-view stereo to complete such models. Our approach is practical and convenient because when scanning and object or environment one usually takes photographs to texture the resulting model. By using the incomplete scan data as a boundary condition, we use a variational multi-view approach to estimate the missing data.

关键词： Geometry image reconstruction Solid modeling Surface reconstruction Filling Digital images Stereo image processing Surface fitting image sensors Interpolation

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Non-iterative quantitative SPECT reconstructions with a reduced-size system matrix

Non-iterative quantitative SPECT reconstructions with a redu...

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IEEE Nuclear Science Symposium/Medical Imaging conference

作者： Shcherbinin, S. Ceher, A. Univ British Columbia Med Imaging Res Grp Dept Radiol Vancouver BC V5Z 1M9 Canada

ISBN: (纸本)9781424409228

Our research objective is to design a clinically viable computational procedure that will provide quantitative activity distribution to be used in dosimetry calculations for internal radiotherapy (IRT). To this end, we studied the accuracy of images reconstructed with the qSPECT method which includes CT-based attenuation correction, 3D resolution recovery, and analytical scatter calculation. During these investigations we found that determination of object boundaries is often difficult due to the substantial edge "smoothing" caused by the MLEM reconstruction process which also created distortions in voxelized activity distributions. By contrast, methods based on direct matrix inversion may reconstruct sharper images. In parallel, it is well known fact that some tumor SPECT studies are characterized by an intense tracer uptake which is localized in a relatively small area, while the remaining parts of the body have only low background. That fact served as a motivation/justification for developing and testing of the non-iterative reconstruction technique based on solving the reduced system of equations. Special algorithm was designed to extract only this part of the initial system matrix which corresponds to the volume of interest (vOI) to be reconstructed. The penalized least squares approach with Tikhonov-type regularizer was employed to solve this reduced system. Preliminary comparison of our partial penalized least squares (PPLS) method with MLEM using Monte Carlo and analytical simulations of hot object with no or low (up to 11%) background shows improved accuracy of the activity estimation when using PPLS. In experiments with 11% background, this method, however, produces artifacts at the boundaries of the vOI. Nevertheless, even in these unfavorable situations it could be employed as an element (hidden from the clinical user) of quantitative data processing.

关键词： SPECT tumor dosimetry quantitation system matrix simulation image reconstruction

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A robust iterative super-resolution reconstruction of image sequences using a Tukey's biweigth Bayesian approach with fast affine block-based registration

A robust iterative super-resolution reconstruction of image ...

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IEEE International conference onMultimedia and Expo, ICME 2007

作者： Patanavijit, v. Sermwuthisarn, P. Jitapunkul, S. Faculty of Engineering Assumption University Bangkok Thailand Faculty of Engineering Chulalongkorn University Thailand

ISBN: (纸本)1424410177

The success of SRR algorithms is highly dependent on the accuracy of the model of the imaging process. When the data or noise model assumptions do not faithfully describe the measure data, the estimator perfonnance degrades. Most noise models used in SRR algorithms are based on AWGN model at low power therefore SRR algorithms can effectively apply only on the image sequence that is corrupted by AWGN. The real noise models that corrupt the measure sequence are unknown;consequently, SRR algorithm using L1 or L2 norm may degrade the image sequence rather than enhance it. Therefore, the robust norm applicable to several noise and data models is desired in SRR algorithms. This *** an alternate SRR approach based on the stochastic regularization technique of Bayesian MAP estimation by minimizing a cost function. The Tukey nonn is used for measuring the difference between the projected estimate of the high-resolution image and each low resolution image, removing outliers in the data and Tikhonov regularization is used to remove artifacts from the final answer and improve the rate of convergence. Due to real sequences and complex motion sequences, the fast affine block-based registration is used for registration step of SRR. The experimental results show that the proposed SRR can apply on real sequence such as Suzie sequence and confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods based on Ll and L2 norm for a several noise models such as AWGN, Poisson and Salt & Pepper Noise. ©2007 IEEE.

关键词： Cost functions

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4D coronary artery reconstruction based on retrospectively gated rotational angiography: first in-human results

4D coronary artery reconstruction based on retrospectively g...

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Medical Imaging 2007 conference

作者： Movassaghi, B. Grass, M. Schaefer, D. Rasche, v. Wink, O. Schoonenberg, G. Chen, J. Y. Garcia, J. A. Groves, B. M. Messenger, J. C. Carroll, J. D. Philips Res N Amer 345 Scarborough Rd Briarcliff Manor NY 10510 USA Philips Res Europe Res Sect Med Imaging Syst D-22335 Hamburg Germany Univ Colorado Hlth Sci Ctr Div Cardiol Denver CO 80262 USA

ISBN: (纸本)9780819466273

A method is proposed that allows for a fully automated computation of a series of high-resolution volumetric reconstructions of a patient's coronary arteries based on a single rotational acquisition. During the 7.2 second acquisition the coronary arteries are injected with contrast material while the imaging system rotates around the patient to obtain a series of X-ray projection images over an angular range of 180 degrees. Based on the simultaneously recorded ECG-signal the projection images corresponding to the same cardiac cycle can be utilized to reconstruct three-dimensional (3D) high-spatial-resolution angiograms of the coronary arteries in multiple (3D+t) cardiac phases within the cardiac cycle. The proposed acquisition protocol has been applied to 22 patients and the tomograpic reconstructions depicted the main arteries as well as the main bifurcations in multiple cardiac phases in all enrolled patients. For the first time, this feasibility study shows that a three-dimensional description of the coronary arteries can be obtained intraprocedurally in a conventional interventional suite by means of tomographic reconstruction from projection images without any user interaction.

关键词： Arteries Angiography 3D image processing X-rays 3D image reconstruction 3D acquisition data acquisition X-ray imaging Sensors Imaging systems

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