Super-resolution image reconstruction with edge adaptive weight in video sequence

Ji Yong Kwon; Du Sic Yoo; Jong Hyun Park; Se Hyeok Park; Moon Gi Kang

doi:10.1117/12.905368

Super-resolution image reconstruction with edge adaptive weight in video sequence

Ji Yong Kwon, Du Sic Yoo, Jong Hyun Park, Se Hyeok Park, Moon Gi Kang

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. Image up-scaling algorithm is important issue since original input source is limited in transferring within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.

Original language	English
Title of host publication	Proceedings of SPIE-IS and T Electronic Imaging - Image Processing
Subtitle of host publication	Algorithms and Systems X; and Parallel Processing for Imaging Applications II
DOIs	https://doi.org/10.1117/12.905368
Publication status	Published - 2012
Event	Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II - Burlingame, CA, United States Duration: 2012 Jan 23 → 2012 Jan 25

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	8295
ISSN (Print)	0277-786X

Other

Other	Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Country/Territory	United States
City	Burlingame, CA
Period	12/1/23 → 12/1/25

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.905368

Cite this

Kwon, J. Y., Yoo, D. S., Park, J. H., Park, S. H., & Kang, M. G. (2012). Super-resolution image reconstruction with edge adaptive weight in video sequence. In Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II Article 82950M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8295). https://doi.org/10.1117/12.905368

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title = "Super-resolution image reconstruction with edge adaptive weight in video sequence",

abstract = "Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. Image up-scaling algorithm is important issue since original input source is limited in transferring within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.",

author = "Kwon, {Ji Yong} and Yoo, {Du Sic} and Park, {Jong Hyun} and Park, {Se Hyeok} and Kang, {Moon Gi}",

year = "2012",

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series = "Proceedings of SPIE - The International Society for Optical Engineering",

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Kwon, JY, Yoo, DS, Park, JH, Park, SH & Kang, MG 2012, Super-resolution image reconstruction with edge adaptive weight in video sequence. in Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II., 82950M, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, Burlingame, CA, United States, 12/1/23. https://doi.org/10.1117/12.905368

Super-resolution image reconstruction with edge adaptive weight in video sequence. / Kwon, Ji Yong; Yoo, Du Sic; Park, Jong Hyun et al.
Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II. 2012. 82950M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8295).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Kang, Moon Gi

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N2 - Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. Image up-scaling algorithm is important issue since original input source is limited in transferring within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.

AB - Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. Image up-scaling algorithm is important issue since original input source is limited in transferring within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.

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Kwon JY, Yoo DS, Park JH, Park SH, Kang MG. Super-resolution image reconstruction with edge adaptive weight in video sequence. In Proceedings of SPIE-IS and T Electronic Imaging - Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II. 2012. 82950M. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.905368

Super-resolution image reconstruction with edge adaptive weight in video sequence

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