Experimental Study on Image Reconstruction from Spatial Correlation-based Optical Flow Motion Vector over Non Gaussian Noise Contamination using Reversed Confidential with Bilateral Filter
Experimental Study on Image Reconstruction from Spatial Correlation-based Optical Flow Motion Vector over Non Gaussian Noise Contamination using Reversed Confidential with Bilateral Filter
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2016
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eng
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application/pdf
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6 pages
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Vincent Mary School of Engineering
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International conference organized by Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association, Thailand. June 28 – July 1, 2016
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Abstract
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 filter on spatial correlation-based optical flow is mainly
focused to determined the best condition to apply this model
with. The result in image reconstruction from motion vector is
used in performance comparison with traditional noise tolerance
models by using Peak Signal to Noise Ratio (PSNR) as a primary
index for studying.