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Petersson, Stefan
Publications (2 of 2) Show all publications
Petersson, S., Grahn, H. & Rasmusson, J. (2016). Color demosaicing using structural instability. In: Proceedings - 2016 IEEE International Symposium on Multimedia, ISM 2016: . Paper presented at 18th IEEE International Symposium on Multimedia, (ISM), San José, USA (pp. 541-544). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Color demosaicing using structural instability
2016 (English)In: Proceedings - 2016 IEEE International Symposium on Multimedia, ISM 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 541-544Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a new metric for approximating structural instability in Bayer image data. We show that the metric can be used to identify and classify validity of color correlation in local image regions. The metric is used to improve interpolation performance of an existing state of-the-art single pass linear demosaicing algorithm, with virtually no impact on computational GPGPU complexity and performance. Using four different image sets, the modification is shown to outperform the original method in terms of visual quality, by having an average increase in PSNR of 0.7 dB in the red, 1.5 dB in the green and 0.6 dB in the blue channel respectively. Because of fewer high-frequency artifacts, the average output data size also decreases by 2.5%. © 2016 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
Bayer, Demosaicing, GPGPU, Linear, Structural instability, Program processors
National Category
Computer Systems
Identifiers
urn:nbn:se:bth-14066 (URN)10.1109/ISM.2016.0119 (DOI)000399166000109 ()2-s2.0-85015170613 (Scopus ID)9781509045709 (ISBN)
Conference
18th IEEE International Symposium on Multimedia, (ISM), San José, USA
Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2018-02-02Bibliographically approved
Petersson, S. & Grahn, H. (2014). Improving image quality by SSIM based increase of run-length zeros in GPGPU JPEG encoding. In: Conference Record of the Asilomar Conference on Signals Systems and Computers: . Paper presented at 48h Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA (pp. 1714-1718). IEEE Computer Society
Open this publication in new window or tab >>Improving image quality by SSIM based increase of run-length zeros in GPGPU JPEG encoding
2014 (English)In: Conference Record of the Asilomar Conference on Signals Systems and Computers, IEEE Computer Society, 2014, p. 1714-1718Conference paper, Published paper (Refereed)
Abstract [en]

JPEG encoding is a common technique to compress images. However, since JPEG is a lossy compression certain artifacts may occur in the compressed image. These artifacts typically occur in high frequency or detailed areas of the image. This paper proposes an algorithm based on the SSIM metric to improve the experienced quality in JPEG encoded images. The algorithm improves the quality in detailed areas by up to 1.29 dB while reducing the quality in less detailed areas of the image, thereby increasing the overall experienced quality without increasing the image data size. Further, the algorithm can also be used to decrease the file size (by up to 43%) while preserving the experienced image quality. Finally, an efficient GPU implementation is presented. © 2014 IEEE.

Place, publisher, year, edition, pages
IEEE Computer Society, 2014
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
Keywords
Algorithms; Encoding (symbols); Image coding; Image quality; Program processors, Compressed images; File sizes; GPU implementation; High frequency HF; Image data; Lossy compressions; Run length, Image compression
National Category
Computer Sciences
Identifiers
urn:nbn:se:bth-10673 (URN)10.1109/ACSSC.2014.7094760 (DOI)000370964900309 ()2-s2.0-84940492806 (Scopus ID)978-1-4799-8297-4 (ISBN)
Conference
48h Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA
Projects
BigData@BTH - Scalable resource-efficient systems for big data analytics
Funder
Knowledge Foundation
Available from: 2015-09-16 Created: 2015-09-15 Last updated: 2018-02-02Bibliographically approved
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