4x4 High-Magnification Image Reconstruction Based on Hybrid of Multi-frame SR Approach and Image Super Resolve Algorithm
4x4 High-Magnification Image Reconstruction Based on Hybrid of Multi-frame SR Approach and Image Super Resolve Algorithm
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2015-11
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eng
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application/pdf
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5 pages
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IEEE International Conference on Intelligent Informatics and BioMedical Sciences (ICIIBMS 2015), Okinawa, Japan, Nov. 2015, 342-346
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Abstract
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 each
polluted low resolution images. Next, the 2x2 magnified image is
reconstructed by using image super resolve algorithm based on
the high-frequency image prediction to be the 4x4 magnified
image. In the performance testing section, the outcomes on both
benchmark (in PSNR) and virtual quality, contrasting with
previous classical algorithms from the research literature (such
as a classical interpolation technique, a classical SRR and an
image super resolve algorithm), expose that the proposed hybrid
framework has the better performance in both benchmark (in
PSNR) and virtual quality.