An Alternative SR Spatial Enhancement Based on Adaptive Meridian Filter and GOM Registration for Severe Noisy Blurred Videos
An Alternative SR Spatial Enhancement Based on Adaptive Meridian Filter and GOM Registration for Severe Noisy Blurred Videos
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2015-08
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eng
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application/pdf
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5 pages
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The Twelveth Internaional Conference on Electrical Engineering 2015
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Abstract
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, this paper
proposed the alternative SR spatial enhancement using adaptive
meridian filter and GOM (General Observation Model)
registration for severe noisy blurred videos. The adaptive
meridian filter is a robust filter, which is desire for controlling
high power outlier, and GOM is a high precision registration
technique, which is desired for registering a fast spatial sequence.
For proving the proposed performance, the simulated
experiments are done in several environments as following: 1.
Additive White Gaussian Noise (AWGN) at SNR=15, 17.5, 20,
22.5, 25dB; 2. Poisson Noise; 3. Multiplicative White Gaussian
Noise (Speckle Noise) at V=0.01, 0.02, 0.03; 4. Salt and Pepper
Noise at D=0.005, 0.010, 0.015. The proposed enhancement
algorithm shows that the PSRN of the enhanced image is higher
than the SR spatial enhancement based on classical filter with
classical registration and GOM registration.