Authors:
Seiichi Gohshi
1
and
Isao Echizen
2
Affiliations:
1
Kogakuin University, Japan
;
2
National Institute of Informatics, Japan
Keyword(s):
Image Enhancement, Super Resolution Reconstruction, Frequency Domain, Real-time.
Related
Ontology
Subjects/Areas/Topics:
Design and Implementation of Signal Processing Systems
;
Image and Video Processing, Compression and Segmentation
;
Multidimensional Signal Processing
;
Multimedia
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Telecommunications
Abstract:
Super resolution image reconstruction (SRR) is a typical super resolution (SR) technology that has been researched with varying results. The SRR algorithm was initially proposed for still images. It uses many low-resolution images to reconstruct a high-resolution image. Unfortunately, in practice, we rarely have a sufficient number of low-resolution images for SRR to work. Usually, there is only one (or a few) blurry images. On the other hand, there is a need to improve blurry images in applications ranging from security and photo
restoration to zooming functions and countless other examples related to the printing industry. Recently, SRR was extended to video sequences that have many similar frames that can be used as low-resolution images to reconstruct high-resolution frames. In normal SRR, one reconstructs a high-resolution image from lowresolution images sampled from one high-resolution image, but in the video application, the low-resolution video frames are not taken from highe
r resolution ones. This paper proposes a novel resolution improvement method that works without such a high- resolution image. Its algorithm is simple and can be applied to a single
image and real-time video systems.
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