In this paper, we propose an improved image dehazing algorithm using dark channel prior and Multi-Scale Retinex. Main improvement lies in automatic and fast acquisition of transmission map of the scene. We implement the Multi-scale Retinex algorithm on the luminance component in YCbCr space, obtain a pseudo transmission map whose function is similar to the transmission map in original approach. Combining with the haze image model and the dark channel prior, we can recover a high quality haze-free image. Compared with the original method, our algorithm has two main advantages: (i) no user interaction is needed, and (ii) restoring the image much faster while maintaining comparable dehazing performance.

Cloud computing is the key and frontier field of the current domestic and international computer technology, workflow task scheduling plays an important part of cloud computing, which is a policy that maps tasks to appropriate resources to execute. Effective task scheduling is essential for obtaining high performance in cloud environment. In this paper, we present a workflow task scheduling algorithm based on the resources' fuzzy clustering named FCBWTS. The major objective of scheduling is to minimize makespan of the precedence constrained applications, which can be modeled as a directed acyclic graph. In FCBWTS, the resource characteristics of cloud computing are considered, a group of characteristics, which describe the synthetic performance of processing units in the resource system, are defined in this paper. With these characteristics and the execution time influence of the ready task in the critical path, processing unit network is pretreated by fuzzy clustering method in order to realize the reasonable partition of processor network. Therefore, it largely reduces the cost in deciding which processor to execute the current task. Comparison on performance evaluation using both the case data in the recent literature and randomly generated directed acyclic graphs shows that this algorithm has outperformed the HEFT, DLS algorithms both in makespan and scheduling time consumed. fuzzy theory to analyze resource performance, preprocess the resources, and achieve the integration and classification of a large number of resources, then we improve the HEFT list sort and complete the task scheduling according to their priority. PROBLEM DESCRIPTIONS Cloud computingCloud computing is hinting at a future in which we would not compute on local computers but on centralized facilities operated by third-party compute and storage utilities [5]. Computing pioneer John McCarthy predicted that 'computation may someday be organized as a public utility', and went on to speculate how this might occur [3,4]. There is little consensus on how to define the cloud computing, many computing researchers and practitioners have attempted to define clouds in various ways.Buyya et al.[22] thought that cloud computing was a new and promising paradigm delivering services as computing utilities. Clouds were designed to provide services to external users, providers needed to be compensated for sharing their resources and capabilities. Wang L.Z et al.[23] defined the science cloud computing system, they pointed out that cloud computing could not only provide the hardware service HaaS (Hardware as a service), software service SaaS (software as a service) and data resource service DaaS (Data as a service), but also could provide the platform service PaaS (platform as a service) to the user. So the users would submit their own on-demand to the computing platform about the hardware configuration, software installation, data access requirements, and so on. With the increasing demand for process automation in the cloud, there is a requirement to create ...

Abstract-Existing view-invariant gait recognition methods encounter difficulties due to limited number of available gait views and varying conditions during training. This paper proposes gait partial similarity matching that assumes a 3-dimensional (3D) object shares common view surfaces in significantly different views. Detecting such surfaces aids the extraction of gait features from multiple views. 3D parametric body models are morphed by pose and shape deformation from a template model using 2-dimensional (2D) gait silhouette as observation. The gait pose is estimated by a level set energy cost function from silhouettes including incomplete ones. Body shape deformation is achieved via Laplacian deformation energy function associated with inpainting gait silhouettes. Partial gait silhouettes in different views are extracted by gait partial region of interest elements selection and re-projected onto 2D space to construct partial gait energy images. A synthetic database with destination views and multi-linear subspace classifier fused with majority voting are used to achieve arbitrary view gait recognition that is robust to varying conditions. Experimental results on CMU, CASIA B, TUM-IITKGP, AVAMVG and KY4D and datasets shows the efficacy of the propose method.Index Terms-gait; person identification; 3D gait model; partial similarity matching.

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Abstract-In this paper, we propose a simple but effective method for visibility restoration from a single image. The main advantage of the proposed algorithm is no user interaction is needed, this allows our algorithm to be applied for practical applications, such as surveillance, intelligent vehicle, etc. Another advantage compared with others is its speed, since the cost of obtaining transmission map is greatly cut down by using Retinex algorithm on luminance component. A comparative study and quantitative evaluation is proposed with the main present-day methods which demonstrate that similar or better quality results are obtained.

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Abstract:We present two haze removal algorithms for single image based on haziness analysis. One algorithm regards haze as the veil layer, and the other takes haze as the transmission. The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer. The latter employs guided filter to obtain the refined haze transmission and separates it from the original image. The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast. A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods. On the top of haze removal, several applications of the haze transmission including image refocusing, haze simulation, relighting and 2-dimensional (2D) to 3-dimensional (3D) stereoscopic conversion are also implemented.