Now showing items 1-20 of 40

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    4x4 High-Magnification Image Reconstruction Based on Hybrid of Multi-frame SR Approach and Image Super Resolve Algorithm 

    Vorapoj Patanavijit (2015-11)

    From tremendously soliciting high quality and high resolution images, sundry image reconstruction algorithms have been researched and implemented during the last fifteen years, especially for high-magnification image reconstructions. In this paper, we develop high-magnification image reconstruction based on hybrid of a multi-frame SR approach and an image super resolve algorithm for 4x4 magnifying in resolution. First, a group of polluted low resolution images are amalgamated for 2x2 magnifying in resolution and suppressing the noise in ...
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    An Adaptive And Statistical Efficiency Myriad Filter For A Recursive Image Reconstruction Using a Multi-Frame SRR Algorithm With A Stochastic Regularization For Video Sequences 

    Vorapoj Patanavijit (2015)

    In real applied implementations, a collection of classical linear filtering theories, for example, a Median filter and a Mean filter, can be only applied to the Gaussian noise environments due to the fact that these linear filters usually gives the poor performance under the presence of non-Gaussian noise environments. Because of the motion estimation blunder and observation process error, which are usually caused from real electronic noise, non-accurate optical devices or mathematical simplification models of observed process systems, the ...
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    An Alternative Single-Image Super Resolution Framework Employing High Frequency Prediction Using A Robust Huber Rational Function 

    Kornkamol Thakulsukannant; Vorapoj Patanavijit (2015-11)

    In general prospective, SI-SR or Single-Image Super-Resolution, which is one of the most useful algorithms of Super Resolution-Reconstruction (SRR) algorithms, is a mathematical procedure for acquiring a high-resolution image from only one coarse-resolution image, which is usually computed by Digital Image Processing (DIP). Even thought there have been substantially researched during the last decade, Single - Image Super-Resolution for applying on real implementations still keeps throw down the gauntlet. One of the practical Single- Image ...
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    An Alternative SR Spatial Enhancement Based on Adaptive Meridian Filter and GOM Registration for Severe Noisy Blurred Videos 

    Kornkamol Thakulsukanant; Vorapoj Patanavijit (2015-08)

    Commonly, filtering technique and the video registration technique are two main significance factors of a video SR (Super Resolution) enhancement algorithm. First, the classical filtering technique is based on a linear filter such as mean or median filter that are only suitable for noiseless or low power noise. Later, classical video registration techniques are usually based on a simple translation model because of the fast computation and easy implementation thereby this registration has high precision error. To get over both problems, ...
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    An Alternative Technique using Median Filter for Image Reconstruction based on Partition Weighted Sum Filter 

    Vorapoj Patanavijit (2016-06)

    In this paper, we propose an alternative technique for image reconstruction which it is combined existing methods for better performance in spatial domain using the median (MED) filter based on partition weighted sum (PWS) filter. Four noise models are considered including additive white Gaussian noise (AWGN), poission noise (PN), salt and pepper noise (SPN) and speckle noise (SN) under different image types such as aerial image, face image, scenic image, and text image. The simulation results show that the median based partition weighted ...
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    Bidirectional Confidential with Bilateral Filter on Local Based Optical Flow for Image Reconstruction under Noisy Condition 

    Darun Kesrarat; Vorapoj Patanavijit (2015)

    More than a decade, Optical flow is relevant in many areas such as video coding and compression, robot vision, object tracking and segmentation, and super resolution reconstruction. By the result of the motion vector from optical flow, reduction the error stands a problem especially under noisy condition. Many models have been proposed to reduce the error and bilateral is one of the popular models. This paper introduces the model of bilateral filter in combination with bidirectional confidential over simple local based optical flow where ...
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    The Bilateral Denoising Performance Influence of Window, Spatial and Radiometric Variance 

    Vorapoj Patanavijit (2015-08)

    In the research operation of Digital Signal Processing (DSP) and Digital Image Processing (DIP), one of the most essential obstacles is the image denoise algorithm by the reason of a very large demand of high quality noise-free images therefore there are many image denoise algorithms have been invented in the time of two decades. Bilateral filter is one of the most impressive and feasible algorithms, which is usually applied for denoise propose, but the performance of the Bilateral filter is substantially bank on three parameters: spatial ...
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    Comparative Experimental Exploration of Robust Norm Functions for Iterative Super Resolution Reconstructions under Noise Surrounding 

    Vorapoj Patanavijit (2015)

    In DIP (Digital Image Processing) research society, the multi-frame SRR (Super Resolution Reconstruction) algorithm has grown to be the momentous theme in the last ten years because of its cost e ectiveness and its superior spectacle. Consequently, for a multi-frame SRR algorithm which is commonly comprised of a Bayesian ML (Maximum Likelihood) approach and a regularization technique into the unify SRR framework, numerous robust norm functions (which have both redescending and non-redescending in uence functions) have been commonly ...
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    Computational Tutorial of Steepest Descent Method and Its Implementation in Digital Image Processing 

    Vorapoj Patanavijit (2013)

    In the last decade, optimization techniques have extensively come up as one of principal signal processing techniques, which are used for solving many previous intractable problems in both digital signal processing (DSP) problems and digital image processing (DIP) problem. Due to its low computational complexity and uncomplicated implementation, the Gradient Descent (GD) method [1] is one of the most popular optimization methods for problems, which can be formulated as a differentiable multivariable functions. The GD method is ubiquitously ...
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    A Conceptual Framework of Super Resolution Reconstruction (SRR) Techniques 

    Vorapoj Patanavijit (2016)

    Typically, a spatial resolution (Pixel per Area) is an important factor used to define the image quality. Due to the dramatically advance of digital image processing in this decade, high resolution (HR) images are in demand because HR images give more detail and information that directly impact their application performance. Today, there are several techniques that can capture high resolution images such as resolution increment by reducing pixel side. Consequently this high resolution sensor is so expensive and do not proper for general ...
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    Conceptual Framework of Super Resolution Reconstruction Based on Frequency Domain From Aliased Multi-Low Resolution Images: Theory Part 

    Vorapoj Patanavijit (2016)

    Typically, a spatial resolution (Pixel per Area) is an important factor used to define the image quality. Due to the dramatically advance of digital image processing in this decade, high resolution (HR) images are in demand because HR images give more detail and information that directly impact their application performance. Today, there are several techniques that can capture high resolution images such as resolution increment by reducing pixel side. Consequently this high resolution sensor is so expensive and do not proper for general applications. ...
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    Empirical Exploration Achievement of Noise Removal Algorithm Based on Trilateral Filter for Both Gaussian and Impulsive Noise Ambiance 

    Vorapoj Patanavijit (2016-06)

    Although the Bilateral filter is one of the most realistic and virtuoso noise removal algorithms, which is often proposed for Gaussian noise in 1998, the Bilateral filter (BF) ineffectively works under the impulsive noise. Consequently, Trilateral filter (which is a modification Bilateral filter) was first proposed by Roman Garnett et al. in 2005 and this filter is based on the hybrid consisting of Bilateral filter and Rank-Ordered Absolute Differences (ROAD) statistic for automatically attenuating or excluding of Gaussian and impulsive ...
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    Experimental Analysis of Performance Comparison on Both Linear Filter and Bidirectional Con dential Technique for Spatial Domain Optical Flow Algorithm 

    Darun Kesrarat; Vorapoj Patanavijit (2013)

    Optical flow is a method for classifying the density velocity or motion vector (MV) in a degree of pixel basis for motion classification of image in video sequences. In actual situation, many unpleasant situations usually generate noises over the video sequences. These unpleasant situations corrupt the performance in efficiency of optical flow. In turn to increase the efficiency of the MV, this research work proposes the performance comparison on linear filter and bidirectional confidential technique for spatial domain optical flow ...
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    Experimental Efficiency Analysis in Robust models of Spatial Correlation Optical Flow Methods under Non Gaussian Noisy Contamination 

    Darun Kesrarat; Vorapoj Patanavijit (2013-05)

    In this paper, we present a performance analysis of several robust models of spatial correlation optical flow algorithms including an original spatial correlation optical flow (SCOF), bidirectional for high reliability optical flow (BHR), gradient orientation information for robust motion estimation (GOI), and robust and high reliability based on bidirectional symmetry and median motion estimation (RHR) under the non Gaussian noise conditions. The simulated results are tested on 4 different in foreground and background movement characteristics ...
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    An Experimental Performance Analysis of Image Reconstruction Techniques under Both Gaussian and Non-Gaussian Noise Models 

    Vorapoj Patanavijit (2012-07)

    Recently, the images reconstruction approaches are very essential in digital image processing (DIP), especially in terms of removing the noise contaminations and recovering the content of images. Each image reconstruction approach has different mathematical models. Therefore a performance of individual reconstruction approach is varied depending on several factors such as image characteristic, reconstruction mathematical model, noise model and noise intensity. Thus, this paper presents comprehensive experiments based on the comparisons ...
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    Experimental Study Efficiency of Robust Models of Lucas-Kanade Optical Flow Algorithms in the Present of Non-Gaussian Noise 

    Vorapoj Patanavijit (2012-07)

    This paper presents experimental efficiency study of noise tolerance model of spatial optical flow based on LucasKanade (LK) algorithms such as original LK with kernel of Barron, Fleet, and Beauchemin (BFB), confidence based optical flow algorithm for high reliability (CRR), robust motion estimation methods using gradient orientation information (RGOI), and a novel robust and high reliability for LucasKanade optical flow algorithm using median filter and confidence based technique (NRLK) under several NonGaussian Noise. These experiment ...
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    Experimental Study on Image Reconstruction from Spatial Correlation-based Optical Flow Motion Vector over Non Gaussian Noise Contamination using Reversed Confidential with Bilateral Filter 

    Darun Kesrarat; Vorapoj Patanavijit (2016)

    In motion estimation, noise is a verity to degrade the performance in optical flow for determining motion vector. This paper examines the performance of noise tolerance model in spatial correlation-based optical flow for image reconstruction from motion vector where the source sequences are contaminated by non Gaussian noise. There are Poisson Noise, Salt & Pepper Noise, and Speckle Noise. In the experiment, several standard sequences in different styles are used and the applied combination model of reversed confidential with bilateral ...
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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, block ...
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    Fast Image Restoration Technique for Car License Plate Based on PWS filter Using 2DPCA Algorithm 

    Vorapoj Patanavijit (2013)

    In this paper, we propose the algorithm that used to identify car license plate that the capture images come in degraded version by combining a PWS filtering technique with a 2DPCA algorithm. From experiment results, our algorithm has three advantages. First, it can be operated to the image directly without transforming the structure of the image, which is two dimensional data, into a vector. Second, it can be implemented with less burden of computation and requires less memory. At last, less time is required to restore the image.
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