Recent Submissions

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    Performance evaluation of L1, L2 and SL0 on compressive sensing based on stochastic estimation technique 

    Ha, Pham Hong; Vorapoj Patanavijit (2010-05)

    In this paper, we proposed 2 algorithms based on L1 and L2 norm estimator to recover the signal by using just few components. Moreover we comprehensively present the recovery algorithm based on L1, L2 and SL0 for digital signal or image under some several noise models from their incomplete observation. The proposed algorithm is used with a matrix that the number of row is much fewer than the column. The algorithm states that if signal or image is sufficient sparse, we can recover it from small number of linear measurement by solving convex p...
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    A fast image recovery using compressive sensing technique with block based orthogonal matching pursuit 

    Vorapoj Patanavijit; Parichat Sermwuthisarn; Supatana Auethavekiat (2009-12)

    Traditionally, the problems of applying Orthogonal Matching Pursuit (OMP) to large images are its high computing time and its requirement for a large matrix. In this paper, we propose a fast image recovery algorithm by dividing the image into block of nxn pixels and applying OMP to each nxn block instead of the entire image. The key idea is that small matrix requires less computing time and less memory. In the experiment, the block based OMP was applied to three standard test images: Lena, Mandrill and Pirate. Compared to standard OMP, bloc...
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    Video enhancement using a robust iterative SRR based on a German&McClure stochastic estimation with a general observation model 

    Vorapoj Patanavijit (2010-05)

    This paper proposes the novel robust SRR algorithm that can be effectively applied on the sequence that are corrupted by various noise models and can be applied on the real or standard sequence. First, the proposed SRR algorithm is based on the German&McClure norm that used for measuring the difference between the projected estimate of the high quality image and each low high quality image and for removing outliers in the data. Second, in order to cope with real video sequences and complex motion sequences, the proposed SRR is based on a gene...
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    Multiframe resolution-enhancement using a robust iterative SRR based on leclerc stochastic technique 

    Vorapoj Patanavijit (2009-10)

    This paper proposes a multiframe resolution-enhancement using a robust iterative SRR (Super-Resolution Reconstruction) for applying on images that is corrupted by several nose models. Typically, the success of SRR algorithms is highly dependent on the model accuracy regarding the imaging process. The real noise models corrupting the measure sequence are unknown hence SRR algorithms using L1 or L2 norm may degrade the image sequence rather than enhance it. The proposed enhancement algorithm is based on the stochastic regularization SRR techni...
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    Video enhancement using a robust iterative SRR based on andrew's sine regularization technique 

    Vorapoj Patanavijit (2009-12)

    In this paper, we propose a alternative robust video enhancement algorithm using SRR based on the regularization ML technique. First, the classical registration process is used to estimate the relationship between the reference frame and other neighboring frames. Subsequently, the Andrew's Sine norm is used for measuring the difference between the projected estimate of the high quality image and each low high quality image and for removing outliers in the data. Moreover, Tikhonov regularization is incorporated in the proposed framework in or...
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    Video enhancement using a robust iterative SRR based on leclerc stochastic estimation 

    Vorapoj Patanavijit (2009-09)

    Recent results in SRR (Super Resolution Reconstruction) demonstrate that the fusion of a sequence of low-resolution noisy blurred images can produce a higher-resolution image or sequence. Since noise is always present in practical acquisition systems, almost video enhancement algorithms are developed assuming AWGN model for the corruption noise. When the underlying video measurements are corrupted by other noise models such as Poisson Noise, impulsive Noise (Salt & Pepper) and Speckle Noise, the enhancement algorithms fail to recover a close ...
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    Co-existance between AC-distribution and DC-distribution: in the view of appliances 

    Kittiphan Techakittiroj; Virach Wongpaibool (2009)

    This work demonstrates the possibility of using the available-in-market appliances in a DC-distribution system. This demonstration also represents an alternative migration from AC-distribution to DC-distribution. DC-distribution has been shown to be more efficient and provided good power quality in a distribution system. The power supply technology in the modern appliances makes the possibility of an appliance to be used in either both AC-distribution and DC-distribution without any modification. Appliances are tested by using an AC-source ...
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    Pattern matching by optimizing load in a reflectarray antenna 

    Bhattarai, Amulya; Wallace, Jon (2009-10)

    A novel method to match radiation pattern of a reflectarray antenna by optimizing the load is presented in this paper. By varying the load attached to each element in a reflectarray the reflection coefficient at each element is varied, which varies the overall radiation pattern of the reflectarray antenna. This paper addresses the synthesis problem, "What is the optimal loading configuration given a target radiation pattern?" Mathematical solution for computing the optimal load for a target radiation pattern is presented. ADS and MATLAB sim...

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