Authors:
Seiichi Gohshi
and
Michikazu Akasu
Affiliation:
Kogakuin University, Japan
Keyword(s):
Super Resolution, Super Resolution Image Reconstruction, Low Resolution Image, High Resolution Image, Blur.
Related
Ontology
Subjects/Areas/Topics:
Design and Implementation of Signal Processing Systems
;
Digital Audio and Video Broadcasting
;
Image and Video Processing, Compression and Segmentation
;
Interactive Multimedia: Games and Digital Television
;
Multimedia
;
Multimedia and Communications
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Telecommunications
Abstract:
Super Resolution (SR) is a technique for improving the resolution of digital images. Super Resolution Image
Reconstruction (SRR) is one of the most common SR techniques. However, in addition to SRR, there are
several other techniques to improve image resolution. A technique called Blind Deconvolution (BD) has been
used to process out of focus images in the field of astronomy. When BD was first described, in the 1970s, it
was not considered to be a viable candidate to be used for SR. However, the process of improving resolution
is very similar to that of focusing images. SRR and BD both use iterations to create a high quality image from
low resolution images. Compared with SRR, BD comes with some disadvantages. For example, algorithms
sometimes cause divergences or limit cycles which means that the high resolution image cannot be obtained.
In this study, we describe a method of fixing the issues that prevent BD from achieving a high-resolution image
using simulation to increa
se its stability. The output from the improved algorithm for BD is compared with
the current SR technique, SRR. We show that the BD technique is in fact superior to SRR.
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