Skip to main content
Erschienen in: International Journal of Computer Vision 6/2020

09.01.2020

Siamese Dense Network for Reflection Removal with Flash and No-Flash Image Pairs

verfasst von: Yakun Chang, Cheolkon Jung, Jun Sun, Fengqiao Wang

Erschienen in: International Journal of Computer Vision | Ausgabe 6/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This work addresses the reflection removal with flash and no-flash image pairs to separate reflection from transmission. When objects are covered by glass, the no-flash image usually contains reflection, and thus flash is used to enhance transmission details. However, the flash image suffers from the specular highlight on the glass surface caused by flash. In this paper, we propose a siamese dense network (SDN) for reflection removal with flash and no-flash image pairs. SDN extracts shareable and complementary features via concatenated siamese dense blocks. We utilize an image fusion block for the SDN to fuse the intermediate output of two branches. Since severe information loss occurs in the specular highlight, we detect the specular highlight in the flash image based on gradient of the maximum chromaticity. Through observations, flash causes various artifacts such as tone distortion and inhomogeneous brightness. Thus, with synthetic datasets we collect 758 pairs of real flash and no-flash image pairs (including their ground truth) by different cameras to gain generalization. Various experiments show that the proposed method successfully removes reflections using flash and no-flash image pairs and outperforms state-of-the-art ones in terms of visual quality and quantitative measurements. Besides, we apply the SDN to color/depth image pairs and achieve both color reflection removal and depth filling.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Anhänge
Nur mit Berechtigung zugänglich
Literatur
Zurück zum Zitat Agrawal, A., Raskar, R., Nayar, S. K., & Li, Y. (2005). Removing photography artifacts using gradient projection and flash-exposure sampling. ACM Transactions on Graphics (TOG), 24(3), 828–835.CrossRef Agrawal, A., Raskar, R., Nayar, S. K., & Li, Y. (2005). Removing photography artifacts using gradient projection and flash-exposure sampling. ACM Transactions on Graphics (TOG), 24(3), 828–835.CrossRef
Zurück zum Zitat Aksoy, Y., Kim, C., Kellnhofer, P., Paris, S., Elgharib, M., Pollefeys, M., & Matusik, W. (2018). A dataset of flash and ambient illumination pairs from the crowd. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 634–649). Aksoy, Y., Kim, C., Kellnhofer, P., Paris, S., Elgharib, M., Pollefeys, M., & Matusik, W. (2018). A dataset of flash and ambient illumination pairs from the crowd. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 634–649).
Zurück zum Zitat Bromley, J., Guyon, I., LeCun, Y., Säckinger, E., & Shah, R. (1994). Signature verification using a siamese time delay neural network. In Advances in neural information processing systems (pp. 737–744). Bromley, J., Guyon, I., LeCun, Y., Säckinger, E., & Shah, R. (1994). Signature verification using a siamese time delay neural network. In Advances in neural information processing systems (pp. 737–744).
Zurück zum Zitat Camplani, M., & Salgado, L. (2012). Efficient spatio-temporal hole filling strategy for kinect depth maps. In Proceedings of SPIE 8290, three-dimensional image processing (3DIP) and applications II (Vol. 8290, p. 82900E). International Society for Optics and Photonics. Camplani, M., & Salgado, L. (2012). Efficient spatio-temporal hole filling strategy for kinect depth maps. In Proceedings of SPIE 8290, three-dimensional image processing (3DIP) and applications II (Vol. 8290, p. 82900E). International Society for Optics and Photonics.
Zurück zum Zitat Chang, Y., & Jung, C. (2019). Single image reflection removal using convolutional neural networks. IEEE Transactions on Image Processing, 28(4), 1954–1966.MathSciNetCrossRef Chang, Y., & Jung, C. (2019). Single image reflection removal using convolutional neural networks. IEEE Transactions on Image Processing, 28(4), 1954–1966.MathSciNetCrossRef
Zurück zum Zitat Chang, Y., Jung, C., Ke, P., Song, H., & Hwang, J. (2018). Automatic contrast-limited adaptive histogram equalization with dual gamma correction. IEEE Access, 6, 11782–11792.CrossRef Chang, Y., Jung, C., Ke, P., Song, H., & Hwang, J. (2018). Automatic contrast-limited adaptive histogram equalization with dual gamma correction. IEEE Access, 6, 11782–11792.CrossRef
Zurück zum Zitat Chopra, S., Hadsell, R., & Lecun, Y. (2005). Learning a similarity metric discriminatively, with application to face verification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Chopra, S., Hadsell, R., & Lecun, Y. (2005). Learning a similarity metric discriminatively, with application to face verification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
Zurück zum Zitat Diamant, Y., & Schechner, Y.Y. (2008). Overcoming visual reverberations. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1–8). IEEE. Diamant, Y., & Schechner, Y.Y. (2008). Overcoming visual reverberations. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1–8). IEEE.
Zurück zum Zitat Eisemann, E., & Durand, F. (2004). Flash photography enhancement via intrinsic relighting. In ACM Transactions on Graphics (TOG) (Vol. 23, pp. 673–678). ACM. Eisemann, E., & Durand, F. (2004). Flash photography enhancement via intrinsic relighting. In ACM Transactions on Graphics (TOG) (Vol. 23, pp. 673–678). ACM.
Zurück zum Zitat Fan, Q., Yang, J., Hua, G., Chen, B., & Wipf, D. (2017). A generic deep architecture for single image reflection removal and image smoothing. In Proceedings of the IEEE Conference on Computer Vision (ICCV) (pp. 3258–3267). IEEE. Fan, Q., Yang, J., Hua, G., Chen, B., & Wipf, D. (2017). A generic deep architecture for single image reflection removal and image smoothing. In Proceedings of the IEEE Conference on Computer Vision (ICCV) (pp. 3258–3267). IEEE.
Zurück zum Zitat Farid, H., & Adelson, E.H. (1999). Separating reflections and lighting using independent components analysis. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Vol. 1, pp. 262–267). IEEE. Farid, H., & Adelson, E.H. (1999). Separating reflections and lighting using independent components analysis. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Vol. 1, pp. 262–267). IEEE.
Zurück zum Zitat Guo, X., Cao, X., & Ma, Y. (2014). Robust separation of reflection from multiple images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2187–2194). Guo, X., Cao, X., & Ma, Y. (2014). Robust separation of reflection from multiple images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2187–2194).
Zurück zum Zitat Han, B. J., & Sim, J. Y. (2017). Reflection removal using low-rank matrix completion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Han, B. J., & Sim, J. Y. (2017). Reflection removal using low-rank matrix completion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Zurück zum Zitat Han, B. J., & Sim, J. Y. (2018). Glass reflection removal using co-saliency-based image alignment and low-rank matrix completion in gradient domain. IEEE Transactions on Image Processing, 27(10), 4873–4888.MathSciNetCrossRef Han, B. J., & Sim, J. Y. (2018). Glass reflection removal using co-saliency-based image alignment and low-rank matrix completion in gradient domain. IEEE Transactions on Image Processing, 27(10), 4873–4888.MathSciNetCrossRef
Zurück zum Zitat Hang, Z., & Dana, K. (2018). Multi-style generative network for real-time transfer (pp. 349–365). Hang, Z., & Dana, K. (2018). Multi-style generative network for real-time transfer (pp. 349–365).
Zurück zum Zitat He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770–778). He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770–778).
Zurück zum Zitat He, S., & Lau, R. W. (2014). Saliency detection with flash and no-flash image pairs. In Proceedings of the European Conference on Computer Vision (pp. 110–124). Springer. He, S., & Lau, R. W. (2014). Saliency detection with flash and no-flash image pairs. In Proceedings of the European Conference on Computer Vision (pp. 110–124). Springer.
Zurück zum Zitat Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (pp. 2261–2269). Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (pp. 2261–2269).
Zurück zum Zitat Kim, H., Jin, H., Hadap, S., & Kweon, I. (2013). Specular reflection separation using dark channel prior. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1460–1467). Kim, H., Jin, H., Hadap, S., & Kweon, I. (2013). Specular reflection separation using dark channel prior. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1460–1467).
Zurück zum Zitat Kong, N., Tai, Y. W., & Shin, S. Y. (2012). A physically-based approach to reflection separation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 9–16). IEEE. Kong, N., Tai, Y. W., & Shin, S. Y. (2012). A physically-based approach to reflection separation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 9–16). IEEE.
Zurück zum Zitat Levin, A., Lischinski, D., & Weiss, Y. (2004). Colorization using optimization. ACM Transactions on Graphics, 23(3), 689–694.CrossRef Levin, A., Lischinski, D., & Weiss, Y. (2004). Colorization using optimization. ACM Transactions on Graphics, 23(3), 689–694.CrossRef
Zurück zum Zitat Levin, A., & Weiss, Y. (2007). User assisted separation of reflections from a single image using a sparsity prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9), 1647–1654.CrossRef Levin, A., & Weiss, Y. (2007). User assisted separation of reflections from a single image using a sparsity prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(9), 1647–1654.CrossRef
Zurück zum Zitat Li, Y., & Brown, M.S. (2013). Exploiting reflection change for automatic reflection removal. In Proceedings of the IEEE Conference on Computer Vision (pp. 2432–2439). Li, Y., & Brown, M.S. (2013). Exploiting reflection change for automatic reflection removal. In Proceedings of the IEEE Conference on Computer Vision (pp. 2432–2439).
Zurück zum Zitat Li, Y., & Brown, M. S. (2014). Single image layer separation using relative smoothness. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2752–2759). Li, Y., & Brown, M. S. (2014). Single image layer separation using relative smoothness. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2752–2759).
Zurück zum Zitat Li, Y., Tan, R. T., Guo, X., Lu, J., & Brown, M. S. (2016). Rain streak removal using layer priors. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2736–2744). Li, Y., Tan, R. T., Guo, X., Lu, J., & Brown, M. S. (2016). Rain streak removal using layer priors. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2736–2744).
Zurück zum Zitat Lu, C., Drew, M. S., & Finlayson, G. D. (2006). Shadow removal via flash/noflash illumination. In Proceedings of the IEEE Workshop on Multimedia Signal Processing (pp. 198–201). IEEE. Lu, C., Drew, M. S., & Finlayson, G. D. (2006). Shadow removal via flash/noflash illumination. In Proceedings of the IEEE Workshop on Multimedia Signal Processing (pp. 198–201). IEEE.
Zurück zum Zitat Matsui, S., Okabe, T., Shimano, M., & Sato, Y. (2011). Image enhancement of low-light scenes with near-infrared flash images. Information and Media Technologies, 6(1), 202–210. Matsui, S., Okabe, T., Shimano, M., & Sato, Y. (2011). Image enhancement of low-light scenes with near-infrared flash images. Information and Media Technologies, 6(1), 202–210.
Zurück zum Zitat Mertens, T., Kautz, J., & Van Reeth, F. (2009). Exposure fusion: A simple and practical alternative to high dynamic range photography. Computer Graphics Forum, 28(1), 161–171. Mertens, T., Kautz, J., & Van Reeth, F. (2009). Exposure fusion: A simple and practical alternative to high dynamic range photography. Computer Graphics Forum, 28(1), 161–171.
Zurück zum Zitat Nayar, S. K., Fang, X. S., & Boult, T. (1997). Separation of reflection components using color and polarization. International Journal of Computer Vision, 21(3), 163–186.CrossRef Nayar, S. K., Fang, X. S., & Boult, T. (1997). Separation of reflection components using color and polarization. International Journal of Computer Vision, 21(3), 163–186.CrossRef
Zurück zum Zitat Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. (2016). Context encoders: Feature learning by inpainting. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2536–2544). Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. (2016). Context encoders: Feature learning by inpainting. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2536–2544).
Zurück zum Zitat Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., & Toyama, K. (2004). Digital photography with flash and no-flash image pairs. In ACM Transactions on Graphics (TOG) (Vol. 23, pp. 664–672). ACM. Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., & Toyama, K. (2004). Digital photography with flash and no-flash image pairs. In ACM Transactions on Graphics (TOG) (Vol. 23, pp. 664–672). ACM.
Zurück zum Zitat Punnappurath, A., & Brown, M. S. (2019). Reflection removal using a dual-pixel sensor. In The IEEE conference on computer vision and pattern recognition (CVPR). Punnappurath, A., & Brown, M. S. (2019). Reflection removal using a dual-pixel sensor. In The IEEE conference on computer vision and pattern recognition (CVPR).
Zurück zum Zitat Schechner, Y. Y., Kiryati, N., & Basri, R. (2000). Separation of transparent layers using focus. International Journal of Computer Vision, 39(1), 25–39.CrossRef Schechner, Y. Y., Kiryati, N., & Basri, R. (2000). Separation of transparent layers using focus. International Journal of Computer Vision, 39(1), 25–39.CrossRef
Zurück zum Zitat Schechner, Y. Y., Shamir, J., & Kiryati, N. (2000). Polarization and statistical analysis of scenes containing a semireflector. JOSA A, 17(2), 276–284.CrossRef Schechner, Y. Y., Shamir, J., & Kiryati, N. (2000). Polarization and statistical analysis of scenes containing a semireflector. JOSA A, 17(2), 276–284.CrossRef
Zurück zum Zitat Seo, H. J., & Milanfar, P. (2012). Robust flash denoising/deblurring by iterative guided filtering. EURASIP Journal on Advances in Signal Processing, 2012(1), 3.CrossRef Seo, H. J., & Milanfar, P. (2012). Robust flash denoising/deblurring by iterative guided filtering. EURASIP Journal on Advances in Signal Processing, 2012(1), 3.CrossRef
Zurück zum Zitat Shen, J., & Cheung, S. C. S. (2013). Layer depth denoising and completion for structured-light rgb-d cameras. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1187–1194). Shen, J., & Cheung, S. C. S. (2013). Layer depth denoising and completion for structured-light rgb-d cameras. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1187–1194).
Zurück zum Zitat Shih, Y., Krishnan, D., Durand, F., & Freeman, W. T. (2015). Reflection removal using ghosting cues. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3193–3201). Shih, Y., Krishnan, D., Durand, F., & Freeman, W. T. (2015). Reflection removal using ghosting cues. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3193–3201).
Zurück zum Zitat Shirai, K., Okamoto, M., & Ikehara, M. (2011). Noiseless no-flash photo creation by color transform of flash image. In Proceedings of the IEEE Conference on Image Processing (ICIP) (pp. 3437–3440). IEEE. Shirai, K., Okamoto, M., & Ikehara, M. (2011). Noiseless no-flash photo creation by color transform of flash image. In Proceedings of the IEEE Conference on Image Processing (ICIP) (pp. 3437–3440). IEEE.
Zurück zum Zitat Silberman, N., Hoiem, D., Kohil, P., & Fergus, R. (2012). Indoor segmentation and support inference from rgbd images. In Proceedings of the European Conference on Computer Vision. Springer. Silberman, N., Hoiem, D., Kohil, P., & Fergus, R. (2012). Indoor segmentation and support inference from rgbd images. In Proceedings of the European Conference on Computer Vision. Springer.
Zurück zum Zitat Simon, C., & Park, I. K. (2015). Reflection removal for in-vehicle black box videos. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4231–4239). Simon, C., & Park, I. K. (2015). Reflection removal for in-vehicle black box videos. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4231–4239).
Zurück zum Zitat Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:​1409.​1556
Zurück zum Zitat Song, S., Lichtenberg, S. P., & Xiao, J. (2015). Sun rgb-d: A rgb-d scene understanding benchmark suite. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 567–576). Song, S., Lichtenberg, S. P., & Xiao, J. (2015). Sun rgb-d: A rgb-d scene understanding benchmark suite. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 567–576).
Zurück zum Zitat Sun, J., Chang, Y., Jung, C., & Feng, J. (2019). Multi-modal reflection removal using convolutional neural networks. IEEE Signal Processing Letters, 26(7), 1011–1015.CrossRef Sun, J., Chang, Y., Jung, C., & Feng, J. (2019). Multi-modal reflection removal using convolutional neural networks. IEEE Signal Processing Letters, 26(7), 1011–1015.CrossRef
Zurück zum Zitat Sun, J., Kang, S. B., Xu, Z. B., Tang, X., & Shum, H. Y. (2007). Flash cut: Foreground extraction with flash and no-flash image pairs. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1–8). IEEE. Sun, J., Kang, S. B., Xu, Z. B., Tang, X., & Shum, H. Y. (2007). Flash cut: Foreground extraction with flash and no-flash image pairs. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1–8). IEEE.
Zurück zum Zitat Sun, J., Li, Y., Kang, S. B., & Shum, H. Y. (2006). Flash matting. ACM Transactions on Graphics (TOG), 25(3), 772–778.CrossRef Sun, J., Li, Y., Kang, S. B., & Shum, H. Y. (2006). Flash matting. ACM Transactions on Graphics (TOG), 25(3), 772–778.CrossRef
Zurück zum Zitat Szeliski, R., Avidan, S., & Anandan, P. (2000). Layer extraction from multiple images containing reflections and transparency. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Vol. 1, pp. 246–253). IEEE. Szeliski, R., Avidan, S., & Anandan, P. (2000). Layer extraction from multiple images containing reflections and transparency. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Vol. 1, pp. 246–253). IEEE.
Zurück zum Zitat Tan, T., Nishino, K., & Ikeuchi, K. (2003). Illumination chromaticity estimation using inverse-intensity chromaticity space. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Tan, T., Nishino, K., & Ikeuchi, K. (2003). Illumination chromaticity estimation using inverse-intensity chromaticity space. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
Zurück zum Zitat Wan, R., Shi, B., Duan, L. Y., Tan, A. H., & Kot, A. C. (2018). Crrn: Multi-scale guided concurrent reflection removal network. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4777–4785). Wan, R., Shi, B., Duan, L. Y., Tan, A. H., & Kot, A. C. (2018). Crrn: Multi-scale guided concurrent reflection removal network. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4777–4785).
Zurück zum Zitat Wei, K., Yang, J., Fu, Y., Wipf, D., & Huang, H. (2019). Single image reflection removal exploiting misaligned training data and network enhancements. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 8178–8187). Wei, K., Yang, J., Fu, Y., Wipf, D., & Huang, H. (2019). Single image reflection removal exploiting misaligned training data and network enhancements. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 8178–8187).
Zurück zum Zitat Yang, J., Gong, D., Liu, L., & Shi, Q. (2018). Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 654–669). Yang, J., Gong, D., Liu, L., & Shi, Q. (2018). Seeing deeply and bidirectionally: A deep learning approach for single image reflection removal. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 654–669).
Zurück zum Zitat Yang, J., Li, H., Dai, Y., & Tan, R. T. (2016). Robust optical flow estimation of double-layer images under transparency or reflection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1410–1419). Yang, J., Li, H., Dai, Y., & Tan, R. T. (2016). Robust optical flow estimation of double-layer images under transparency or reflection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1410–1419).
Zurück zum Zitat Yang, Y., Ma, W., Zheng, Y., Cai, J. F., & Xu, W. (2019). Fast single image reflection suppression via convex optimization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 8141–8149). Yang, Y., Ma, W., Zheng, Y., Cai, J. F., & Xu, W. (2019). Fast single image reflection suppression via convex optimization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 8141–8149).
Zurück zum Zitat Yi, S., Wang, X., & Tang, X. (2014). Deep learning face representation from predicting 10,000 classes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Yi, S., Wang, X., & Tang, X. (2014). Deep learning face representation from predicting 10,000 classes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
Zurück zum Zitat Yu, L., Xun, C., Cheng, J., & Hu, P. (2017). A medical image fusion method based on convolutional neural networks. In Proceedings of the International Conference on Information Fusion. Yu, L., Xun, C., Cheng, J., & Hu, P. (2017). A medical image fusion method based on convolutional neural networks. In Proceedings of the International Conference on Information Fusion.
Zurück zum Zitat Yu, L., Xun, C., Hu, P., & Wang, Z. (2017). Multi-focus image fusion with a deep convolutional neural network. Information Fusion, 36, 191–207.CrossRef Yu, L., Xun, C., Hu, P., & Wang, Z. (2017). Multi-focus image fusion with a deep convolutional neural network. Information Fusion, 36, 191–207.CrossRef
Zurück zum Zitat Zagoruyko, S., & Komodakis, N. (2015). Learning to compare image patches via convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4353–4361). Zagoruyko, S., & Komodakis, N. (2015). Learning to compare image patches via convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4353–4361).
Zurück zum Zitat Zhang, L., Zhang, L., Mou, X., & Zhang, D. (2011). Fsim: A feature similarity index for image quality assessment. IEEE Transactions on Image Processing, 20(8), 2378–2386.MathSciNetCrossRef Zhang, L., Zhang, L., Mou, X., & Zhang, D. (2011). Fsim: A feature similarity index for image quality assessment. IEEE Transactions on Image Processing, 20(8), 2378–2386.MathSciNetCrossRef
Metadaten
Titel
Siamese Dense Network for Reflection Removal with Flash and No-Flash Image Pairs
verfasst von
Yakun Chang
Cheolkon Jung
Jun Sun
Fengqiao Wang
Publikationsdatum
09.01.2020
Verlag
Springer US
Erschienen in
International Journal of Computer Vision / Ausgabe 6/2020
Print ISSN: 0920-5691
Elektronische ISSN: 1573-1405
DOI
https://doi.org/10.1007/s11263-019-01276-z

Weitere Artikel der Ausgabe 6/2020

International Journal of Computer Vision 6/2020 Zur Ausgabe

Premium Partner