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This paper introduces the using of adaptive Lorentzian norm influence function with the local based optical flow to achieve the robustness in noise interference on the image flow. In particularly, optical flow is the approach to approximate the motion flow from the image flow or video. When the image flow is contaminated or interfered by noise, it directly affects the performance of the optical flow...
Since 1998, the Bilateral filter (BF) has been proposed for suppressing Gaussian noise however the BF cannot functionally perform under the mix noise (that is comprised of Gaussian and S&P noise). Thereby, the Trilateral filter (TF) that is an adapted BF formed on the ROAD (Rank-Ordered Absolute Differences) technique was initially stated by Roman Garnett et al. for self-regulating suppressing...
In optical flow for motion approximation, the productive result in motion vector (MV) is an important issue for video reconstruction. Different in noisy conditions may cause the unreliable result in optical flow algorithms. A lot of robust optical flow algorithm was proposed for noise overthrown to increase the certain result under noisy conditions. This paper focuses on the efficiency of bidirectional...
In almost all circumstances, a digital image with high spatial resolution (so called HR) is often pleasing however it is challenging to obtain due to overpriced cost on equipment devices. Consequently, Super Resolution Reconstruction (SRR) algorithm, which espouses algebraic formulation to obtain HR with reasonable cost, has been one of the most compelling research fields in Computer Vision (CV) and...
Consistently, the classical image enlargement algorithm is a scientific analytical method for producing a better refined resolution image that is frequently required for advanced digital image processing (DIP) from a single lower resolution image that is frequently acquired from digital camera embedded system. Because of its less computation calculation, the Single-Image Super-Resolution (SISR) that...
In order to achieving a fine spatial image, which are algebraically manufactured from either single crude resolution image or many crude resolution images for executing by either computer vision algorithmic techniques or Digital Image Processing (DIP) algorithmic techniques, one of the most practical algorithmic techniques in the image enlargement operation is the Super Resolution Reconstruction (SRR),...
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...
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...
In this paper, we investigate the performance of switching bilateral filter (SBF) influenced by two parameters — radiometric variance (σR) and spatial variance (σS). The SBF can be used to filter Gaussian noise and impulse noise at the same time. For SBF, σR and σS are the two most important factors that affect increasing /decreasing the performance of SBF. Then, we investigate the influence of two...
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...
Noise is one of the main factors that impact the performance of optical flow where the result in motion vector of optical flow is degraded. Many areas in advance require a result of optical flow as a preprocessing such as super resolution image reconstruction, robot vision, motion estimation, edge detection, motion tracking and etc. Then, the accuracy in the result of motion vector from optical flow...
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 4×4 magnifying...
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,...
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,...
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...
In this paper, we present a performance study of bidirectional confidential with median filter on global based (Horn and Schunk) optical flow under non Gaussian noise where several robust models on global based optical flow algorithms are used in comparison including Barron kernel, bidirectional confidence based, and median filter for robust motion estimation. The experiment results are simulated...
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...
Optical flow in image sequences gives essential data on motion structure. It is relevant in several areas such as robot vision, video coding, and super resolution reconstruction. Even though this realm has been concentrated for more than a decade, reduction the glitch in estimation stands a difficult trouble. Many techniques were proposed to enhance the performance and one of the most is bilateral...
The multi-frame SRR (Super Resolution Reconstruction) algorithm has become the significant theme in digital image research society in the last ten years because of its performance and its cost effectiveness hence many robust norm functions (both redescending and non-redescending influence functions) have been usually incorporated in the multi-frame SRR framework, which is combined a stochastic Bayesian...
In block-based motion estimation where the outcome of the motion vector (MV) is used to reconstruct the image, noise is one of the major problems that impact the quality of the performance in image reconstruction. There are several aspects to improve the quality of the reconstructed image but we focus on improvement of the accuracy in MV from existing block-based motion estimation algorithms when...
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