Kim, Chanyul and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2009) Low complexity video compression using moving edge detection based on DCT coefficients. In: 15th international multimedia modeling conference (MMM 09), 7-9 Jan 2009, Sophia-Antipolis, France. ISBN 978-3-540-92891-1
Abstract
In this paper, we propose a new low complexity video compression method based on detecting blocks containing moving edges us- ing only DCT coe±cients. The detection, whilst being very e±cient, also allows e±cient motion estimation by constraining the search process to moving macro-blocks only. The encoders PSNR is degraded by 2dB com- pared to H.264/AVC inter for such scenarios, whilst requiring only 5% of the execution time. The computational complexity of our approach is comparable to that of the DISCOVER codec which is the state of the art low complexity distributed video coding. The proposed method ¯nds blocks with moving edge blocks and processes only selected blocks. The approach is particularly suited to surveillance type scenarios with a static camera.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Low complexity video compression; Moving edge; DCT; |
Subjects: | Computer Science > Video compression Computer Science > Algorithms Computer Science > Digital video |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies |
Published in: | Advances in Multimedia Modeling. Lecture Notes in Computer Science 5371. Springer Berlin / Heidelberg. ISBN 978-3-540-92891-1 |
Publisher: | Springer Berlin / Heidelberg |
Official URL: | http://dx.doi.org/10.1007/978-3-540-92892-8_11 |
Copyright Information: | The original publication is available at www.springerlink.com |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Samsung Electronics, Science Foundation Ireland, SFI 07/CE/I1147 |
ID Code: | 2400 |
Deposited On: | 16 Feb 2009 10:03 by Hyowon Lee . Last Modified 09 Nov 2018 10:08 |
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