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2020 | OriginalPaper | Chapter

Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms

Authors : Jaesung Rim, Haeyun Lee, Jucheol Won, Sunghyun Cho

Published in: Computer Vision – ECCV 2020

Publisher: Springer International Publishing

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Abstract

Numerous learning-based approaches to single image deblurring for camera and object motion blurs have recently been proposed. To generalize such approaches to real-world blurs, large datasets of real blurred images and their ground truth sharp images are essential. However, there are still no such datasets, thus all the existing approaches resort to synthetic ones, which leads to the failure of deblurring real-world images. In this work, we present a large-scale dataset of real-world blurred images and ground truth sharp images for learning and benchmarking single image deblurring methods. To collect our dataset, we build an image acquisition system to simultaneously capture geometrically aligned pairs of blurred and sharp images, and develop a postprocessing method to produce high-quality ground truth images. We analyze the effect of our postprocessing method and the performance of existing deblurring methods. Our analysis shows that our dataset significantly improves deblurring quality for real-world blurred images.

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Appendix
Available only for authorised users
Footnotes
1
We used the libraw library for decoding and demosaicing raw images.
 
Literature
1.
go back to reference Abdelhamed, A., Lin, S., Brown, M.S.: A high-quality denoising dataset for smartphone cameras. In: CVPR, June 2018 Abdelhamed, A., Lin, S., Brown, M.S.: A high-quality denoising dataset for smartphone cameras. In: CVPR, June 2018
2.
go back to reference Ben-Ezra, M., Nayar, S.: Motion deblurring using hybrid imaging. In: CVPR, pp. 657–664 (2003) Ben-Ezra, M., Nayar, S.: Motion deblurring using hybrid imaging. In: CVPR, pp. 657–664 (2003)
3.
go back to reference Cai, J., Zeng, H., Yong, H., Cao, Z., Zhang, L.: Toward real-world single image super-resolution: a new benchmark and a new model. In: ICCV, October 2019 Cai, J., Zeng, H., Yong, H., Cao, Z., Zhang, L.: Toward real-world single image super-resolution: a new benchmark and a new model. In: ICCV, October 2019
5.
go back to reference Chen, G., Zhu, F., Ann Heng, P.: An efficient statistical method for image noise level estimation. In: ICCV, December 2015 Chen, G., Zhu, F., Ann Heng, P.: An efficient statistical method for image noise level estimation. In: ICCV, December 2015
6.
go back to reference Cho, S., Lee, S.: Convergence analysis of map based blur kernel estimation. In: ICCV, pp. 4818–4826, October 2017 Cho, S., Lee, S.: Convergence analysis of map based blur kernel estimation. In: ICCV, pp. 4818–4826, October 2017
7.
go back to reference Cho, S., Lee, S.: Fast motion deblurring. ACM Trans. Graph. 28(5), 145:1–145:8 (2009)CrossRef Cho, S., Lee, S.: Fast motion deblurring. ACM Trans. Graph. 28(5), 145:1–145:8 (2009)CrossRef
8.
go back to reference Cho, S., Wang, J., Lee, S.: Handling outliers in non-blind image deconvolution. In: ICCV (2011) Cho, S., Wang, J., Lee, S.: Handling outliers in non-blind image deconvolution. In: ICCV (2011)
9.
go back to reference Cho, T.S., Paris, S., Horn, B.K.P., Freeman, W.T.: Blur kernel estimation using the radon transform. In: CVPR (2011) Cho, T.S., Paris, S., Horn, B.K.P., Freeman, W.T.: Blur kernel estimation using the radon transform. In: CVPR (2011)
10.
go back to reference Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-D transform-domain collaborative filtering. TIP 16(8), 2080–2095 (2007)MathSciNet Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-D transform-domain collaborative filtering. TIP 16(8), 2080–2095 (2007)MathSciNet
11.
go back to reference Evangelidis, G.D., Psarakis, E.Z.: Parametric image alignment using enhanced correlation coefficient maximization. TPAMI 30(10), 1858–1865 (2008)CrossRef Evangelidis, G.D., Psarakis, E.Z.: Parametric image alignment using enhanced correlation coefficient maximization. TPAMI 30(10), 1858–1865 (2008)CrossRef
12.
go back to reference Fergus, R., Singh, B., Hertzmann, A., Roweis, S.T., Freeman, W.T.: Removing camera shake from a single photograph. ACM Trans. Graph. 25(3), 787–794 (2006)CrossRef Fergus, R., Singh, B., Hertzmann, A., Roweis, S.T., Freeman, W.T.: Removing camera shake from a single photograph. ACM Trans. Graph. 25(3), 787–794 (2006)CrossRef
15.
go back to reference Heikkila, J., Silven, O.: A four-step camera calibration procedure with implicit image correction. In: CVPR, CVPR 1997, p. 1106. IEEE Computer Society, USA (1997) Heikkila, J., Silven, O.: A four-step camera calibration procedure with implicit image correction. In: CVPR, CVPR 1997, p. 1106. IEEE Computer Society, USA (1997)
16.
go back to reference Hirakawa, K., Parks, T.W.: Adaptive homogeneity-directed demosaicing algorithm. TIP 14(3), 360–369 (2005) Hirakawa, K., Parks, T.W.: Adaptive homogeneity-directed demosaicing algorithm. TIP 14(3), 360–369 (2005)
17.
go back to reference Hirsch, M., Schuler, C.J., Harmeling, S., Schölkopf, B.: Fast removal of non-uniform camera shake. In: ICCV, pp. 463–470 (2011) Hirsch, M., Schuler, C.J., Harmeling, S., Schölkopf, B.: Fast removal of non-uniform camera shake. In: ICCV, pp. 463–470 (2011)
18.
go back to reference Hu, Z., Cho, S., Wang, J., Yang, M.: Deblurring low-light images with light streaks. IEEE Trans. Pattern Anal. Mach. Intell. 40(10), 2329–2341 (2018)CrossRef Hu, Z., Cho, S., Wang, J., Yang, M.: Deblurring low-light images with light streaks. IEEE Trans. Pattern Anal. Mach. Intell. 40(10), 2329–2341 (2018)CrossRef
19.
go back to reference Kim, T.H., Lee, K.M.: Segmentation-free dynamic scene deblurring. In: CVPR, pp. 2766–2773, June 2014 Kim, T.H., Lee, K.M.: Segmentation-free dynamic scene deblurring. In: CVPR, pp. 2766–2773, June 2014
20.
go back to reference Köhler, R., Hirsch, M., Mohler, B., Schölkopf, B., Harmeling, S.: Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7578, pp. 27–40. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33786-4_3CrossRef Köhler, R., Hirsch, M., Mohler, B., Schölkopf, B., Harmeling, S.: Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7578, pp. 27–40. Springer, Heidelberg (2012). https://​doi.​org/​10.​1007/​978-3-642-33786-4_​3CrossRef
21.
go back to reference Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J.: DeblurGAN: blind motion deblurring using conditional adversarial networks. In: CVPR, June 2018 Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J.: DeblurGAN: blind motion deblurring using conditional adversarial networks. In: CVPR, June 2018
22.
go back to reference Kupyn, O., Martyniuk, T., Wu, J., Wang, Z.: DeblurGAN-v2: deblurring (orders-of-magnitude) faster and better. In: ICCV, October 2019 Kupyn, O., Martyniuk, T., Wu, J., Wang, Z.: DeblurGAN-v2: deblurring (orders-of-magnitude) faster and better. In: ICCV, October 2019
23.
go back to reference Lai, W.S., Huang, J.B., Hu, Z., Ahuja, N., Yang, M.H.: A comparative study for single image blind deblurring. In: CVPR, June 2016 Lai, W.S., Huang, J.B., Hu, Z., Ahuja, N., Yang, M.H.: A comparative study for single image blind deblurring. In: CVPR, June 2016
24.
go back to reference Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Understanding and evaluating blind deconvolution algorithms. In: CVPR, pp. 1964–1971 (2009) Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Understanding and evaluating blind deconvolution algorithms. In: CVPR, pp. 1964–1971 (2009)
25.
go back to reference Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Efficient marginal likelihood optimization in blind deconvolution. In: CVPR, pp. 2657–2664 (2011) Levin, A., Weiss, Y., Durand, F., Freeman, W.T.: Efficient marginal likelihood optimization in blind deconvolution. In: CVPR, pp. 2657–2664 (2011)
26.
go back to reference Li, F., Yu, J., Chai, J.: A hybrid camera for motion deblurring and depth map super-resolution. In: CVPR (2008) Li, F., Yu, J., Chai, J.: A hybrid camera for motion deblurring and depth map super-resolution. In: CVPR (2008)
27.
go back to reference Lu, B., Chen, J.C., Chellappa, R.: Unsupervised domain-specific deblurring via disentangled representations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2019 Lu, B., Chen, J.C., Chellappa, R.: Unsupervised domain-specific deblurring via disentangled representations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2019
29.
go back to reference Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: ICCV, vol. 2, pp. 416–423 (2001) Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: ICCV, vol. 2, pp. 416–423 (2001)
30.
go back to reference Nah, S., et al.: NTIRE 2019 challenge on video deblurring and super-resolution: dataset and study. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2019 Nah, S., et al.: NTIRE 2019 challenge on video deblurring and super-resolution: dataset and study. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2019
31.
go back to reference Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: CVPR, July 2017 Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: CVPR, July 2017
33.
go back to reference Pan, J., Sun, D., Pfister, H., Yang, M.H.: Blind image deblurring using dark channel prior. In: CVPR, pp. 1628–1636 (2016) Pan, J., Sun, D., Pfister, H., Yang, M.H.: Blind image deblurring using dark channel prior. In: CVPR, pp. 1628–1636 (2016)
34.
go back to reference Plotz, T., Roth, S.: Benchmarking denoising algorithms with real photographs. In: CVPR, July 2017 Plotz, T., Roth, S.: Benchmarking denoising algorithms with real photographs. In: CVPR, July 2017
35.
go back to reference Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. TIP 5(8), 1266–1271 (1996) Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. TIP 5(8), 1266–1271 (1996)
37.
go back to reference Schuler, C.J., Hirsch, M., Harmeling, S., Schölkopf, B.: Learning to deblur. TPAMI 38(7), 1439–1451 (2016)CrossRef Schuler, C.J., Hirsch, M., Harmeling, S., Schölkopf, B.: Learning to deblur. TPAMI 38(7), 1439–1451 (2016)CrossRef
38.
go back to reference Shan, Q., Jia, J., Agarwala, A.: High-quality motion deblurring from a single image. ACM Trans. Graph. 27(3), 73:1–73:10 (2008)CrossRef Shan, Q., Jia, J., Agarwala, A.: High-quality motion deblurring from a single image. ACM Trans. Graph. 27(3), 73:1–73:10 (2008)CrossRef
39.
go back to reference Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., Wang, O.: Deep video deblurring for hand-held cameras. In: CVPR, pp. 237–246, July 2017 Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., Wang, O.: Deep video deblurring for hand-held cameras. In: CVPR, pp. 237–246, July 2017
40.
go back to reference Sun, L., Cho, S., Wang, J., Hays, J.: Edge-based blur kernel estimation using patch priors. In: ICCP (2013) Sun, L., Cho, S., Wang, J., Hays, J.: Edge-based blur kernel estimation using patch priors. In: ICCP (2013)
41.
go back to reference Tai, Y.W., Du, H., Brown, M.S., Lin, S.: Image/video deblurring using a hybrid camera. In: CVPR (2008) Tai, Y.W., Du, H., Brown, M.S., Lin, S.: Image/video deblurring using a hybrid camera. In: CVPR (2008)
42.
go back to reference Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: CVPR, June 2018 Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: CVPR, June 2018
44.
go back to reference Whyte, O., Sivic, J., Zisserman, A., Ponce, J.: Non-uniform deblurring for shaken images. In: CVPR, pp. 491–498 (2010) Whyte, O., Sivic, J., Zisserman, A., Ponce, J.: Non-uniform deblurring for shaken images. In: CVPR, pp. 491–498 (2010)
46.
go back to reference Xu, L., Zheng, S., Jia, J.: Unnatural L0 sparse representation for natural image deblurring. In: CVPR (2013) Xu, L., Zheng, S., Jia, J.: Unnatural L0 sparse representation for natural image deblurring. In: CVPR (2013)
47.
go back to reference Yuan, L., Sun, J., Quan, L., Shum, H.: Image deblurring with blurred/noisy image pairs. In: SIGGRAPH (2007) Yuan, L., Sun, J., Quan, L., Shum, H.: Image deblurring with blurred/noisy image pairs. In: SIGGRAPH (2007)
48.
go back to reference Zhang, H., Dai, Y., Li, H., Koniusz, P.: Deep stacked hierarchical multi-patch network for image deblurring. In: CVPR, June 2019 Zhang, H., Dai, Y., Li, H., Koniusz, P.: Deep stacked hierarchical multi-patch network for image deblurring. In: CVPR, June 2019
49.
go back to reference Zhang, J., et al.: Dynamic scene deblurring using spatially variant recurrent neural networks. In: CVPR, June 2018 Zhang, J., et al.: Dynamic scene deblurring using spatially variant recurrent neural networks. In: CVPR, June 2018
50.
go back to reference Zhang, Z.: A flexible new technique for camera calibration. TPAMI 22(11), 1330–1334 (2000)CrossRef Zhang, Z.: A flexible new technique for camera calibration. TPAMI 22(11), 1330–1334 (2000)CrossRef
51.
go back to reference Zhou, S., Zhang, J., Zuo, W., Xie, H., Pan, J., Ren, J.S.: DAVANet: stereo deblurring with view aggregation. In: CVPR, pp. 10988–10997, June 2019 Zhou, S., Zhang, J., Zuo, W., Xie, H., Pan, J., Ren, J.S.: DAVANet: stereo deblurring with view aggregation. In: CVPR, pp. 10988–10997, June 2019
52.
go back to reference Šorel, M., Šroubek, F.: Space-variant deblurring using one blurred and one underexposed image. In: ICIP, pp. 157–160 (2009) Šorel, M., Šroubek, F.: Space-variant deblurring using one blurred and one underexposed image. In: ICIP, pp. 157–160 (2009)
Metadata
Title
Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms
Authors
Jaesung Rim
Haeyun Lee
Jucheol Won
Sunghyun Cho
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-58595-2_12

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