Digital image blurring-deblurring process for improved storage and transmission

Paper


Scarmana, Gabriel. 2015. "Digital image blurring-deblurring process for improved storage and transmission." IEEE International Geoscience and Remote Sensing Symposium 2015 (IGARSS 2015): Remote Sensing: Understanding the Earth for a Safer World. Milan, Italy 26 - 31 Jul 2015 Milan, Italy. https://doi.org/10.1109/IGARSS.2015.7325818
Paper/Presentation Title

Digital image blurring-deblurring process for improved storage and transmission

Presentation TypePaper
Authors
AuthorScarmana, Gabriel
Journal or Proceedings TitleProceedings of the IEEE International Geoscience and Remote Sensing Symposium 2015 (IGARSS 2015)
ERA Conference ID45008
Number of Pages4
Year2015
Place of PublicationMilan, Italy
ISBN9781479979295
Digital Object Identifier (DOI)https://doi.org/10.1109/IGARSS.2015.7325818
Web Address (URL) of Paperhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7325818&tag=1
Conference/EventIEEE International Geoscience and Remote Sensing Symposium 2015 (IGARSS 2015): Remote Sensing: Understanding the Earth for a Safer World
IEEE International Geoscience and Remote Sensing Symposium
Event Details
IEEE International Geoscience and Remote Sensing Symposium
IGARSS
International Geoscience and Remote Sensing Symposium (IGARSS)
Rank
C
C
C
C
C
C
Event Details
IEEE International Geoscience and Remote Sensing Symposium 2015 (IGARSS 2015): Remote Sensing: Understanding the Earth for a Safer World
Event Date
26 to end of 31 Jul 2015
Event Location
Milan, Italy
Abstract

This paper investigates the likelihood of using a blurring-deblurring process as a pre-post-processing step in standard image reconstruction and compression. As such, the paper relates to image coding and compression systems whereby an original image can be transmitted or stored in a coded and compressed representation which renders it blurred and degraded.
The compressibility of an image increases with the blurring, whereby the relation between compression ratio (CR) and the blurring scale is approximately linear. Hence, by pre-processing and blurring an image before compression, the CR will increase accordingly. The function or process tested here for blurring-deblurring an image is based on a pixel group processing, whereby the original image is sampled at sub-pixel levels. Since the sub-pixel shifts between each pixel group sampling are known exactly,a blurred image is created which can be shown to contain the details of the original image and thereby restored or reconstructed by reversing the blurring process.The complementary effects of increased CR are examined in terms of coding/decoding execution times and the quality of the reconstructed images.

Keywordsimage filtering, image compression, image reconstruction
ANZSRC Field of Research 2020490509. Statistical theory
401302. Geospatial information systems and geospatial data modelling
401304. Photogrammetry and remote sensing
460306. Image processing
Public Notes

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Byline AffiliationsSchool of Civil Engineering and Surveying
Institution of OriginUniversity of Southern Queensland
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