DocumentCode :
2129354
Title :
Super-resolution video reconstruction based on both local and global information
Author :
Lee, I-Hsien ; Tseng, Shau-Yin ; Bose, Nirmal K.
Author_Institution :
ICL, Ind. Technol. Res. Inst., Hsinchu, Taiwan
fYear :
2010
fDate :
2-5 May 2010
Firstpage :
1
Lastpage :
4
Abstract :
Although super-resolution (SR) methods have been successfully used to improve the resolution of video content, these methods estimate high resolution (HR) frames without explicitly use local information. Instead, they minimize the sum of difference between acquired low resolution (LR) images and observation model. On the contrary, adaptive kernel regression estimates each pixel of HR frames independently. It does not consider global optimum while estimating HR frames. In this paper, we proposed an idea of employing adaptive kernel regression on SR methods to improve the quality of super-resolved video frames. It is shown that the proposed idea can provide results with better visual quality and Peak Signal-to-Noise Ratio (PSNR).
Keywords :
image reconstruction; regression analysis; video signal processing; PSNR; global information; kernel regression estimation; local information; peak signal-to-noise ratio; super resolution video reconstruction; Image edge detection; Image resolution; Kernel; PSNR; Pixel; Signal resolution; Strontium; Super-resolution; adaptive kernel regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2010 23rd Canadian Conference on
Conference_Location :
Calgary, AB
ISSN :
0840-7789
Print_ISBN :
978-1-4244-5376-4
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2010.5575208
Filename :
5575208
Link To Document :
بازگشت