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Restoration of rotational motion blurred image based on chebyshev polynomial interpolations

Restoration of rotational motion blurred image based on cheb...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Tianxu Hong, Hanyu Yan, Luxin Zhang, Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

The restoration of rotational motion blurred image involves a lot of interpolations operators in rectangular-to-polar transformation and its inversion of polar-to-rectangular. The technique of interpolation determines the quality of restoration and computational complexity. In this paper, we incorporate orthogonal chebyshev polynomials interpolations into the processing of restoration of rotational motion blurred image, in which the space-variant blurs are decomposed into a series of space-invariant blurs along the blurring paths, and the blurred gray-values of the discrete pixels of the blurring paths are calculated by using of orthogonal chebyshev polynomials' interpolations and the space-variant blurs can be removed along the blurring paths in the polar system. At same way, we use orthogonal chebyshev polynomials' interpolations to perform polar-to-rectangular transformation to put the restored image back to its original rectangular format. In order to overcome the interference of noise, an optimization restoration algorithm based on regularizations is presented, in which non-negative and edge-preserving smoothing are incorporated into the process of restoration. A series of experiments have been performed to test the proposed interpolation method, which show that the proposed interpolations are effective to preserve edges. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Chebyshev polynomials

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New method for laser parameter detection

New method for laser parameter detection

引用

4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement technology and Equipment

作者： Hong, Hanyu Zhang, Huimin Wan, Xiang Zhang, Xiuhua Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of science and technology Wuhan 430074 China

ISBN: (纸本)9780819475435

A new method to detect laser parameter is proposed in this paper. The improved Michelson Interferometer is used as experiment system to detect parameter. In the proposed detection method, the interference images in variant atmosphere visibility by regulating the polarizer in the system simulate the transmissibility of laser. Experimental results show that the proposed scheme can simulate laser parameter in true atmosphere environment and has good application value. © 2009 SPIE.

关键词： Michelson interferometers

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A fast quantum mechanics based contour extraction algorithm

A fast quantum mechanics based contour extraction algorithm

引用

Medical Imaging 2009 - image processing

作者： Lan, Tian Sun, Yangguang Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

A fast algorithm was proposed to decrease the computational cost of the contour extraction approach based on quantum mechanics. The contour extraction approach based on quantum mechanics is a novel method proposed recently by us, which will be presented on the same conference by another paper of us titled "a statistical approach to contour extraction based on quantum mechanics". In our approach, contour extraction was modeled as the locus of a moving particle described by quantum mechanics, which is obtained by the most probable locus of the particle simulated in a large number of iterations. In quantum mechanics, the probability that a particle appears at a point is equivalent to the square amplitude of the wave function. Furthermore, the expression of the wave function can be derived from digital images, making the probability of the locus of a particle available. We employed the Markov Chain Monte Carlo (MCMC) method to estimate the square amplitude of the wave function. Finally, our fast quantum mechanics based contour extraction algorithm (referred as our fast algorithm hereafter) was evaluated by a number of different images including synthetic and medical images. It was demonstrated that our fast algorithm can achieve significant improvements in accuracy and robustness compared with the well-known state-of-the-art contour extraction techniques and dramatic reduction of time complexity compared to the statistical approach to contour extraction based on quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Wave functions

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Recovering 3D Shape of Weak Textured Surfaces

Recovering 3D Shape of Weak Textured Surfaces

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International Conference on Computational science and its Applications (ICCSA)

作者： Mannan Saeed Muhammad Husna Mutahira Abdul Majid Tae-Sun Choi Signal and Image Processing Lab Gwangju Institute of Science and Technology Gwangju Korea

3D shape recovery of the object from its 2D images based on image focus has been an important field of research. Shape from focus (SFF) is one of the passive methods to recover the shape of the object. Mostly,existing approaches work well with dense textured objects; however, they cannot compute depth of weak textured scenes with great precision. In this paper, we propose a new SFF algorithm which improves there covered shape of weak textured objects. The proposed method is experimented and its performance is tested using different image sequences of synthetic and real objects with varying texture. The proposed approach provides better results as compared to previous approaches.

关键词： Surface texture Focusing Layout image sequences Lenses Cameras Laplace equations Optical noise Shape measurement signal processing

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On the non-uniqueness problem and the semi-blind source separation

On the non-uniqueness problem and the semi-blind source sepa...

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2009 IEEE Workshop on Applications of signal processing to Audio and Acoustics, WASPAA 2009

作者： Nesta, Francesco Wada, Ted S. Miyabe, Shigeki Juang, Biing-Hwang Università di Trento Italy Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA United States Department of Information Physics and Computing Graduate School of Information Science and Technology University of Tokyo Japan

ISBN: (纸本)9781424436798

Semi-blind source separation (SBSS) is a special case of the well-known source separation problem when some partial knowledge of the source signals is available to the system. In particular, a batch-wise adaptation in the frequency domain based on the independent component analysis (ICA) can be effectively used to jointly perform source separation and multi-channel acoustic echo cancellation (MCAEC) without double-talk detection. However, the non-uniqueness problem due to the correlated far-end reference signals still affects the SBSS approach. In this paper, we analyze the structure of the SBSS de-mixing matrix and the behavior of a batch on-line adaptation algorithm under two most common far-end mixing conditions. We show that with a proper constraint on the de-mixing matrix, high echo reduction can be achieved just as the misalignment remains relatively low even for the worst-case scenario of single far-end talker and also without any pre-processing procedure to decorrelate the far-end signals. ©2009 IEEE.

关键词： Blind source separation

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Fast on-ship route planning using improved sparse A-star algorithm for UAVs

Fast on-ship route planning using improved sparse A-star alg...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yang, Xin Ding, Mingyue Zhou, Chengping Cai, Chao Yu, Qi Shao, Shuai Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

This paper presented improved Sparse A-Star Search (SAS) algorithm to pursue a fast route planner for Unmanned Aerial Vehicles (UAVs) on-ship applications. Our approach can quickly produce 3-D trajectories composed by a set of successive navigation points from certain known initial locations to predetermined target locations. The result routes are not only ensuring collision avoidance with the environmental obstacles, but also satisfying specific routes constraints and objectives. The experiment results demonstrated the feasibility of the method, which makes our route planner be more useful in real systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

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Accurate 3D shape estimation based on combinatorial optimization

Accurate 3D shape estimation based on combinatorial optimiza...

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IEEE International Conference on image processing

作者： Seong-O Shim Tae-Sun Choi Signal and Image Processing Laboratory School of Information and Mechatronics Gwangju Institute of Science and Technology Gyeongju South Korea

The problem of estimating the three-dimensional (3D) geometry of an object from a sequence of images obtained at different focus settings is called shape from focus (SFF). The conventional SFF methods apply focus measure operator at each pixel using neighboring pixels in the same image frame. However, for an object with complex geometry, such methods cannot compute accurate focus level of a pixel, since the neighboring pixels in an image, taken with small depth of field, do not have the same focus level. In this paper, a novel SFF algorithm based on combinatorial optimization is proposed. After the rough estimate of the shape, we refine the shape iteratively by searching the optimal focus measure of each pixel using neighboring pixels on various image frames. The proposed SFF algorithm shows improvements in both the accuracy of the shape and the computational complexity in comparison to the previous SFF methods.

关键词： Focusing Pixel Shape measurement Iterative algorithms Computational complexity Layout Volume measurement signal processing image processing Mechatronics

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Approximating 3D shape using Bezier surface

Approximating 3D shape using Bezier surface

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

作者： Mannan Saeed Muhammad Muhammad Tariq Mahamood Tae-Sun Choi Signal and Image Processing Laboratory School of Information and Mechatronics Gwangju Institute of Science and Technology Gwangju South Korea

Estimating 3D shape of the object is an important research topic in the area of computer vision, with a wide range of applications. This paper introduces a new method for focused-based passive methods (like SFF) to approximate the 3D shape of the object using Bezier surface. The discrete nature of image sampling results in the loss of information between two consecutive images. Conventional approximation methods optimize or interpolate focus values. We have suggested interpolating depth values instead of focus value over a small patch on the object surface. The method approximates the surface more accurately and also reduces any noise caused by focus measure. The proposed method is tested and analyzed to demonstrate the effectiveness against traditional methods.

关键词： Shape Focusing Computer vision Application software image sampling Approximation methods Optimization methods Noise reduction Noise measurement Testing

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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

引用

MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Classifier-based feature fusion for texture discrimination

Classifier-based feature fusion for texture discrimination

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2009 International Conference on Information Engineering and Computer science, ICIECS 2009

作者： Ma, Jianglin Zhang, Zhouwei Wang, Chengyi Chen, Zhong Remote Sensing Image Processing Laboratory Institute of Remote Sensing Applications CAS Beijing China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424449941

A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA. ©2009 IEEE.

关键词： Discrete wavelet transforms

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