Now showing items 1-4 of 4

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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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    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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    Robust Optical Flow Algorithm Based on Spatial Domain Optical Flow 

    Darun Kesrarat (Assumption University)

    In this paper, we focus on the robustness in noise tolerance of spatial domain optical flow. We present a performance study of bidirectional confidential with median filter on spatial domain optical flow (spatial correlation, local based optical flow, and global based optical flow) under non-Gaussian noise. Several noise tolerance models on spatial domain optical flow are used in comparison. The experimental results are investigated on robustness under noisy condition by using non-Gaussian noise (Poisson Noise, Salt & Pepper noise, ...
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    Tutorial on image reconstruction based on weighted sum (WS) filter approach: from single image to multi-frame image 

    Vorapoj Patanavijit (Assumption University Press, 2009)

    For large magnification factors, the prior classical smoothness leads to overly smooth results with very little high-frequency content. The classical image restorations are failing to reconstruct the desired image. Consequently, the Recognition-Based Restoration is desired for these purposes and one of the most effective techniques is of a weighted sum (WS) filter. This paper reviews the research framework of weighted sum (WS) filter approach for image reconstruction. This research framework first starts with the Hard-Partition-based Weighted ...