Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion

Songhyun Yu, Jechang Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

Motion estimation (ME) has the highest computational complexity in motion-compensated frame rate up-conversion (MC-FRUC). For the real-time implementation of FRUC, a fast ME algorithm is required. In this paper, a new hierarchical ME algorithm for MC-FRUC is proposed. It constructs an image pyramid by dividing the frame into several sub-images according to resolution, and performs ME at the top level to reduce complexity while improving accuracy by selecting multiple motion vector candidates. These candidates are refined at the lower levels, and the final motion vector is selected at the bottom level. Thus, the proposed algorithm obtains an average peak signal-to-noise ratio gain of upto 0.85 dB compared to conventional algorithms with lower computational complexity and yields interpolated images with better visual quality than other methods.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Image Technology, IWAIT 2019
EditorsQian Kemao, Yung-Lyul Lee, Kazuya Hayase, Phooi Yee Lau, Wen-Nung Lie, Lu Yu, Sanun Srisuk
PublisherSPIE
ISBN (Electronic)9781510627734
DOIs
StatePublished - 2019 Jan 1
EventInternational Workshop on Advanced Image Technology 2019, IWAIT 2019 - Singapore, Singapore
Duration: 2019 Jan 62019 Jan 9

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11049
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceInternational Workshop on Advanced Image Technology 2019, IWAIT 2019
CountrySingapore
CitySingapore
Period19/01/619/01/9

Fingerprint

Upconversion
Motion Estimation
Motion estimation
Estimation Algorithms
Motion Vector
Computational complexity
Computational Complexity
Motion
Pyramid
Low Complexity
Signal to noise ratio
Real-time
pyramids
signal to noise ratios

Keywords

  • Frame rate up-conversion
  • image pyramid
  • motion estimation

Cite this

Yu, S., & Jeong, J. (2019). Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion. In Q. Kemao, Y-L. Lee, K. Hayase, P. Y. Lau, W-N. Lie, L. Yu, & S. Srisuk (Eds.), International Workshop on Advanced Image Technology, IWAIT 2019 [1104938] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11049). SPIE. https://doi.org/10.1117/12.2521271
Yu, Songhyun ; Jeong, Jechang. / Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion. International Workshop on Advanced Image Technology, IWAIT 2019. editor / Qian Kemao ; Yung-Lyul Lee ; Kazuya Hayase ; Phooi Yee Lau ; Wen-Nung Lie ; Lu Yu ; Sanun Srisuk. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).
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title = "Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion",
abstract = "Motion estimation (ME) has the highest computational complexity in motion-compensated frame rate up-conversion (MC-FRUC). For the real-time implementation of FRUC, a fast ME algorithm is required. In this paper, a new hierarchical ME algorithm for MC-FRUC is proposed. It constructs an image pyramid by dividing the frame into several sub-images according to resolution, and performs ME at the top level to reduce complexity while improving accuracy by selecting multiple motion vector candidates. These candidates are refined at the lower levels, and the final motion vector is selected at the bottom level. Thus, the proposed algorithm obtains an average peak signal-to-noise ratio gain of upto 0.85 dB compared to conventional algorithms with lower computational complexity and yields interpolated images with better visual quality than other methods.",
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Yu, S & Jeong, J 2019, Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion. in Q Kemao, Y-L Lee, K Hayase, PY Lau, W-N Lie, L Yu & S Srisuk (eds), International Workshop on Advanced Image Technology, IWAIT 2019., 1104938, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11049, SPIE, International Workshop on Advanced Image Technology 2019, IWAIT 2019, Singapore, Singapore, 19/01/6. https://doi.org/10.1117/12.2521271

Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion. / Yu, Songhyun; Jeong, Jechang.

International Workshop on Advanced Image Technology, IWAIT 2019. ed. / Qian Kemao; Yung-Lyul Lee; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Lu Yu; Sanun Srisuk. SPIE, 2019. 1104938 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11049).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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N2 - Motion estimation (ME) has the highest computational complexity in motion-compensated frame rate up-conversion (MC-FRUC). For the real-time implementation of FRUC, a fast ME algorithm is required. In this paper, a new hierarchical ME algorithm for MC-FRUC is proposed. It constructs an image pyramid by dividing the frame into several sub-images according to resolution, and performs ME at the top level to reduce complexity while improving accuracy by selecting multiple motion vector candidates. These candidates are refined at the lower levels, and the final motion vector is selected at the bottom level. Thus, the proposed algorithm obtains an average peak signal-to-noise ratio gain of upto 0.85 dB compared to conventional algorithms with lower computational complexity and yields interpolated images with better visual quality than other methods.

AB - Motion estimation (ME) has the highest computational complexity in motion-compensated frame rate up-conversion (MC-FRUC). For the real-time implementation of FRUC, a fast ME algorithm is required. In this paper, a new hierarchical ME algorithm for MC-FRUC is proposed. It constructs an image pyramid by dividing the frame into several sub-images according to resolution, and performs ME at the top level to reduce complexity while improving accuracy by selecting multiple motion vector candidates. These candidates are refined at the lower levels, and the final motion vector is selected at the bottom level. Thus, the proposed algorithm obtains an average peak signal-to-noise ratio gain of upto 0.85 dB compared to conventional algorithms with lower computational complexity and yields interpolated images with better visual quality than other methods.

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Yu S, Jeong J. Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion. In Kemao Q, Lee Y-L, Hayase K, Lau PY, Lie W-N, Yu L, Srisuk S, editors, International Workshop on Advanced Image Technology, IWAIT 2019. SPIE. 2019. 1104938. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2521271