DocumentCode :
256747
Title :
An integrated framework for both compression noise reduction and super-resolution
Author :
Seok Bong Yoo ; Kyuha Choi ; Sehyeok Park ; Jong Beom Ra
Author_Institution :
Dept. of Electr. Eng., KAIST, Daejeon, South Korea
fYear :
2014
fDate :
7-10 Oct. 2014
Firstpage :
161
Lastpage :
162
Abstract :
Even though super-resolution is a promising technique, it can cause unwanted increase of compression noises, if it is applied to an image coded with a low bit-rate. To solve this problem, we propose an integrated framework to reduce compression noises and to recover high-frequency components of a coded low-resolution image. The framework effectively combines two patch-based algorithms, a patch-matching-based 3-D filtering algorithm and an example-based super-resolution algorithm, based on the combination of 3-D transform coefficients. Experimental results demonstrate that the proposed framework successfully improves the resolution while alleviating compression noises in the images coded with low bit-rates.
Keywords :
data compression; filtering theory; image coding; image denoising; image matching; image resolution; transforms; 3D transform coefficient; compression noise reduction; example-based superresolution algorithm; image coded low-resolution imaging; patch-based algorithm; patch-matching-based 3D filtering algorithm; Discrete cosine transforms; Hafnium; Image coding; Image resolution; PSNR; Signal processing algorithms; compression noises; integrated framework; super-resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics (GCCE), 2014 IEEE 3rd Global Conference on
Conference_Location :
Tokyo
Type :
conf
DOI :
10.1109/GCCE.2014.7031117
Filename :
7031117
Link To Document :
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