This paper describes a novel method to enhance underwater images by image dehazing. Scattering and color change are two major problems of distortion for underwater imaging. Scattering is caused by large suspended part...
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This paper describes a novel method to enhance underwater images by image dehazing. Scattering and color change are two major problems of distortion for underwater imaging. Scattering is caused by large suspended particles, such as turbid water which contains abundant particles. Color change or color distortion corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths, rendering ambient underwater environments dominated by a bluish tone. Our key contributions are proposed a new underwater model to compensate the attenuation discrepancy along the propagation path, and proposed a fast joint trigonometric filtering dehazing algorithm. The enhanced images are characterized by reduced noised level, better exposedness of the dark regions, improved global contrast while the finest details and edges are enhanced significantly. In addition, our method is comparable to higher quality than the state-of-the-art methods by assuming in the latest image evaluation systems. (C) 2013 Elsevier Ltd. All rights reserved.
Total variation method has been widely used in image processing, however, it produces undesirable staircase effect. Recently, the two-step method has been used to alleviate the staircase effect successfully. Combined ...
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Total variation method has been widely used in image processing, however, it produces undesirable staircase effect. Recently, the two-step method has been used to alleviate the staircase effect successfully. Combined with a new vector field and an edge indicator function, a novel variational model is proposed in this paper. Unlike the two-step method, the proposed model contains only one energy functional, that is to say, the new vector field and the reconstructed image are interwoven. Due to using the information of the restored image fully, the new vector field is more accurate than the normal vector field, and the reconstructed image is also better than that in the two-step method. To solve the new model, we design a primal-dual method to simulate the minimization problem. The numerical experiments show that the new model can obtain significant improvement not only in noise removal but also in avoiding staircase effect. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed framework, low-cost static cameras are deployed to cover a large region, moving targets are detect...
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We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed framework, low-cost static cameras are deployed to cover a large region, moving targets are detected and then tracked using corresponding algorithms, target positions are estimated by making use of the geometrical relationships among those cameras after calibrating those cameras, and finally, for each target, its position estimates obtained from different cameras are unified into the world coordinate system. This system can function as complementary positioning information sources to realize moving target positioning in indoor or outdoor environments when global navigation satellite system (GNSS) signals are unavailable. The experiments are carried out using practical indoor and outdoor environment data, and the experimental results show that the systematic framework and inclusive algorithms are both effective and efficient.
A new noise reduction algorithm HeNLM-LA is proposed. It is a modification of the non-local means algorithm using Hermite functions expansion of pixel neighborhoods. The filtering strength parameter is automatically a...
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A new noise reduction algorithm HeNLM-LA is proposed. It is a modification of the non-local means algorithm using Hermite functions expansion of pixel neighborhoods. The filtering strength parameter is automatically adjusted proportionally to the local noise level. An algorithm for local noise level estimation is based on edge modeling;it suppresses high-amplitude edges in the map of local image variance.
For an undirected complex network made up with vertices and edges, we developed a fast computing algorithm that divides vertices into different groups by maximizing the standard "modularity" measure of the r...
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For an undirected complex network made up with vertices and edges, we developed a fast computing algorithm that divides vertices into different groups by maximizing the standard "modularity" measure of the resulting partitions. The algorithm is based on a simple constrained power method which maximizes a quadratic objective function while satisfying given linear constraints. We evaluated the performance of the algorithm and compared it with a number of state-of-the-art solutions. The new algorithm reported both high optimization quality and fast running speed, and thus it provided a practical tool for community detection and network structure analysis.
Holographic algorithms with matchgates are a novel approach to design polynomial time computation. They use Kasteleyn's algorithm for perfect matchings, and more importantly a holographic reduction. The two fundam...
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Holographic algorithms with matchgates are a novel approach to design polynomial time computation. They use Kasteleyn's algorithm for perfect matchings, and more importantly a holographic reduction. The two fundamental parameters of a holographic reduction are the domain size k of the underlying problem and the basis size l. A holographic reduction transforms the computation to matchgates by a linear transformation that maps to (a tensor product space of) a linear space of dimension 2(l). We prove a sharp basis collapse theorem, which shows that for domain size 3 and 4, all non-trivial holographic reductions can be expressed with a basis of size 1 or 2, respectively. The main proof techniques are Matchgate Identities and a Group Property of matchgate signatures. (C) 2014 Elsevier Inc. All rights reserved.
With the development of multimedia, the technology of image and video is growing from 2D to 3D, thus interactivity is going to become a main character of future multimedia technology. Virtual view synthesis, known as ...
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With the development of multimedia, the technology of image and video is growing from 2D to 3D, thus interactivity is going to become a main character of future multimedia technology. Virtual view synthesis, known as the analogue expression to the real world, is one of the key techniques in interactive 3D video systems. This paper proposes a new algorithm of virtual view synthesis, which is based on disparity estimation. Considering two rectified input reference images that are taken in the same scene simultaneously, the accurate dense disparity maps are gained as the first step. Then image interpolation is used to synthesize certain virtual view image and reverse mapping is adopted to fill up the holes which are formed in previous process. By defining a position parameter, this algorithm can produce results at an arbitrary view between the two original views. Experimental results illustrate the superiority of the proposed method. (C) 2014 Elsevier Ltd. All rights reserved.
A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extract...
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A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extracted in succession. Each newly extracted feature is the optimal feature that maximizes the trace ratio criterion function in the subspace orthogonal to the space spanned by the previous extracted features.
Intelligent video surveillance network has many practical applications such as human tracking, vehicle tracking, and event detection. In this paper, an active multicamera network framework is designed for human detect...
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Intelligent video surveillance network has many practical applications such as human tracking, vehicle tracking, and event detection. In this paper, an active multicamera network framework is designed for human detection and tracking by optimizing the cameras collaborating control. A multicamera collaborating control algorithm is proposed based on Bayes network to minimize the number of PTZ cameras with control and optimize the cameras' field of view. Hybrid human local feature transform selected by AdaBoost algorithm is adopted to improve the tracking precision. Experimental results on real world environment indicate the effectiveness and efficiency of proposed framework and algorithm.
This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, w...
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This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, we created the cost-reliability-delay model (CRD model) that consisted of two parts: the physical topology part aimed at obtaining the networks with the maximum reliability under constrained cost, while the logical topology part focused on the communication paths yielding minimum delay based on the physical topology delivered from upper level. We also suggested a method to solve the CRD model, which combined the genetic algorithm and the Floyd-Warshall algorithm. Finally, we used a practical example to verify the accuracy and the effectiveness of the CRD model and further applied the novel method on a train with six carriages.
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