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Qiaochu Li, Qikun Guo , Saboya Yang and Jiaying Liu*

2013. Scale-Compensated Nonlocal Mean Super Resolution. Qiaochu Li, Qikun Guo , Saboya Yang and Jiaying Liu*. Institute of Computer Science and Technology Peking University. Outline. Introduction Multi-frame SR Nonlocal means SR (NLM SR) Our Algorithm Scale-detector

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Qiaochu Li, Qikun Guo , Saboya Yang and Jiaying Liu*

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  1. 2013 Scale-Compensated Nonlocal MeanSuper Resolution Qiaochu Li, QikunGuo, Saboya Yang and Jiaying Liu* Institute of Computer Science and Technology Peking University

  2. Outline • Introduction • Multi-frame SR • Nonlocal means SR (NLM SR) • Our Algorithm • Scale-detector • Scale-Compensated NLM • Experimental results • Conclusion & Future work

  3. Outline • Introduction • Multi-frame SR • Nonlocal means SR (NLM SR) • Our Algorithm • Scale-detector • Scale-Compensated NLM • Experimental results • Conclusion & Future work

  4. Multi-Frame SR • Converge low resolution images into a high resolution image • Direct motion estimation • INVALIDin complex situation

  5. Nonlocal Means SR • Image content repeats in neighborhoods • In temporal and spatial domains • Probabilistic motion estimation • Weighted average NLM weight distribution. The weights go from 1 (white) to 0 (black).

  6. Problem • Scale may be varied in frames by zooming. • Camera motion • Object motion Scale changing effects in adjacent frames. (a) Two adjacent frames, (b) some critical areas of the frames.

  7. Outline • Introduction • Multi-frame SR • Nonlocal means SR (NLM SR) • Our Algorithm • Scale-detector • Scale-Compensated NLM • Experimental results • Conclusion & Future work

  8. Scale-Detector • Using SIFT descriptor to compute scales Partial matched keypoints and the corresponding scale values.

  9. Verification • Verification of scale-detector Always appears region (a) (b) The performances of scale-detector in different standard scales and different resolutions, (a) average error by frame scale, (b) average error by frame resolution.

  10. Scale-Compensated NLM • SC NLM finds more similar patches Comparison of unmodified and modified patch-extractor in patch matching.

  11. Procedures • Overview of SC NLM Scale-detector Patch extraction & modification NLMSR

  12. Experimental Results • Downsample • Blurred using 3×3 uniform mask • Decimated by 3×factor • Additive noise with standard deviation 2 • Objective measurement • Subjective measurement

  13. Experimental Results • 3×, Objective measurement (PSNR)

  14. Experimental Results • 3×, Subjective measurement (SSIM)

  15. Experimental Results a) Result of whole frame. b) High resolution frame. c) NLM SR. d) SC NLM.

  16. Experimental Results a) Result of whole frame. b) High resolution frame. c) NLM SR. d) SC NLM

  17. Outline • Introduction • Multi-frame SR • Nonlocal means SR (NLM SR) • Our Algorithm • Scale-detector • Scale-Compensated NLM • Experimental results • Conclusion & Future work

  18. Conclusion • When patches are convert into SAME SCALE, • we can find more SIMILAR PATCHES, • we can use more COMPLEMENTARY INFORMATION • to reconstruct a HIGH RESOLUTION & QUANLITY IMAGE.

  19. Future Work • More accurate scale-detector • Segmentation based scale-detector • Combination of rotation and translation-invariant algorithm • Rotation-invariant measurement • Translation-invariant measurement

  20. Thank You！

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