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A component-driven distributed framework for real-time video dehazing

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Abstract

Traditional dehazing techniques, as a well studied topic in image processing, are now widely used to eliminate the haze effects from individual images. However, the state-of-the-art dehazing algorithms may not provide sufficient support to video analytics, as a crucial pre-processing step for video-based decision making systems (e.g., robot navigation), due to poor coherence and low processing efficiency of the present algorithms. This paper presents a new framework, particularly designed for video dehazing, to output coherent results in real time, with two novel techniques. Firstly, we decompose the dehazing algorithms into three generic components, namely transmission map estimator, atmospheric light estimator and haze-free image generator. They can be simultaneously processed by multiple threads in the distributed system, such that the processing efficiency is optimized by automatic CPU resource allocation based on the workloads. Secondly, a cross-frame normalization scheme is proposed to enhance the coherence among consecutive frames, by sharing the parameters of atmospheric light from consecutive frames in the distributed computation platform. The combination of the above three components enables our framework to generate highly consistent and accurate dehazing results in real-time, by using only 5 PCs connected by Ethernet.

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References

  1. Ancuti CO, Ancuti C, Hermans C, Bekaert P (2010) A fast semiinverse approach to detect and remove the haze from a single image. In: Conference on asian conference on computer vision (ACCV), vol 6493, pp 501–514

  2. Dong XM, Hu XY, Peng SL, Wang DC (2010) Single color image dehazing using sparse priors. Int Conf Image Process (ICIP) 119(5):3593–3596

    Google Scholar 

  3. Fattal R (2008) Single image dehazing. ACM Trans Graph (TOG) 27(3):1–9

    Article  Google Scholar 

  4. Fu TZJ, Ding J, Ma RTB, Winslett M, Yang Y, Zhang ZJ, Pei Y, Ni BB Livetraj: real-time trajectory tracking over live video streams. In: ACM international conference on multimedia, pp 777–780. https://dl.acm.org/citation.cfm?id=2807401&CFID=1017797602&CFTOKEN=67128231

  5. Ge C, Sun Z, Wang N, Xu K (2014) Energy management in cross-domain content delivery networks: a theoretical perspective. IEEE Trans Netw Serv Manag 11(3):264–277

    Article  Google Scholar 

  6. Gibson KB, Vo DT, Nguyen TQ (2012) An investigation of dehazing effects on image and video coding. IEEE Trans Image Process (TIP) 12(2):662–673

    Article  MathSciNet  MATH  Google Scholar 

  7. Gulisano V, Jimnez-Peris R, Patino-Martnez M, Soriente C, Valduriez P (2012) Streamcloud: an elastic and scalable data stream system. IEEE Trans Parallel Distrib Syst (TPDS) 23(12):2351–2365

    Article  Google Scholar 

  8. He K, Sun J, Tang X (2011) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell (TPAMI) 33(12):2341–2353

    Article  Google Scholar 

  9. He K, Sun J, Tang X (2013) Guided image filtering. IEEE Trans Pattern Anal Mach Intell (TPAMI) 35(6):1397–1409

    Article  Google Scholar 

  10. Kim TK, Paik JK, Kang BS (1998) Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering. IEEE Trans Consum Electron 44(1):82–87

    Article  Google Scholar 

  11. Kim JY, Kim LS, Hwang SH (2001) An advanced contrast enhancement using partially overalapped sub-block histogram equalization. Circ Syst Video Technol 11(4):475–484

    Article  Google Scholar 

  12. Kokkonis G, Psannis KE, Roumeliotis M, Ishibashi Y (2015) Efficient algorithm for transferring a real-time HEVC stream with haptic data through the internet. J Real-Time Image Process 12(2):343–355

    Article  Google Scholar 

  13. Kokkonis G, Psannis KE, Roumeliotis M, Dan S (2017) Real-time wireless multisensory smart surveillance with 3D-HEVC streams for internet-of-things (IoT). J Supercomput 73(3):1–19

    Article  Google Scholar 

  14. Kopf J, Neubert B, Chen B, Cohen M, Cohen-Or D, Deussen O, Uyttendaele M, Lischinski D (2008) Deep photo: model-based photograph enhancement and viewing. ACM Trans Graph 27(5):116

    Article  Google Scholar 

  15. Kratz L, Nishino K (2009) Factorizing scene albedo and depth from a single foggy image. In: IEEE international conference on computer vision (ICCV), vol 30, issue 2, pp 1701–1708

  16. Kulkarni S, Bhagat N, Fu M, Kedigehalli V et al (2015) Twitter heron: stream processing at scale. In: ACM Sigmod international conference on management of data, pp 239–250. https://dl.acm.org/citation.cfm?id=2742788

  17. Levin A, Lischinski D, Weiss Y (2008) A closed-form solution to natural image matting. IEEE Trans Pattern Anal Mach Intell (TPAMI) 30(2):228–242

    Article  Google Scholar 

  18. Li ZW, Tan P, Tan RT, Zou DP, Zhou SZ, Cheong LF (2015) Simultaneous video defogging and stereo reconstruction. In: IEEE computer society conference on computer vision and pattern recognition (CVPR), pp 4988–4997

  19. Lu H, Li Y, Nakashima S, Serikawa S (2016) Single image dehazing through improved atmospheric light estimation. Multimed Tools Appl 75(24):17081–17096

    Article  Google Scholar 

  20. Lv X, Chen W, Shen IF (2010) Real-time dehazing for image and video. In: Pracific conference on computer graphics and applications (PG), pp 62–69

  21. Memos VA, Psannis KE (2015) Encryption algorithm for efficient transmission of HEVC media. J Real-Time Image Process 12(2):1–10

    Google Scholar 

  22. Meng G F, Wang Y, Duan J, Xiang S, Pan C (2013) Efficient image dehazing with boundary constraint and contextual regularization. In: IEEE international conference on computer vision (ICCV), pp 617–624. http://ieeexplore.ieee.org/document/6751186/

  23. Narasimhan SG, Nayar SK (2003) Contrast restoration of weather degraded images. IEEE Trans Pattern Anal Mach Intell (TPAMI) 25(6):713–724

    Article  Google Scholar 

  24. Narasimhan SG, Nayar SK (2003) Interactive (de) weathering of an image using physical models. In: IEEE workshop color photometric methods computing vision, vol 6, p 1

  25. Nishino K, Kratz L, Lombardi S (2012) Bayesian defogging. Int J Comput Vis 98(3):263–278

    Article  MathSciNet  Google Scholar 

  26. Pei SC, Lee TY (2012) Nighttime haze removal using color transfer pre-processing and dark channel prior. In: International conference on image processing (ICIP), pp 957–960. http://ieeexplore.ieee.org/document/6467020/

  27. Psannis KE (2009) Efficient redundant frames encoding algorithm for streaming video over error prone wireless channels. IEICE ELEX J 6(21):1497–1502

    Article  Google Scholar 

  28. Psannis KE (2016) HEVC in wireless environments. J Real-Time Image Process 12(2):509–516

    Article  Google Scholar 

  29. Psannis KE, Ishibashi Y (2006) Impact of video coding on delay and jitter in 3G wireless video multicast services. Eurasip Journal on Wireless Communications and Networking 1–7

  30. Psannis KE, Ishibashi Y (2008) Efficient flexible macroblock ordering technique. IEICE Trans Commun 91(8):2692–2701

    Article  Google Scholar 

  31. Psannis KE, Ishibashi Y (2008) Enhanced H.264/AVC stream switching over varying bandwidth networks. IEICE ELEX J 5(19):827–832

    Article  Google Scholar 

  32. Psannis KE, Ishibashi Y (2009) Efficient error resilient algorithm for H.264/AVC: mobility management in wireless video streaming. Springer Telecommun Syst J 41(2):65–76

    Article  Google Scholar 

  33. Psannis KE, Hadjinicolaou MG, Krikelis A (2006) MPEG-2 streaming of full interactive content. IEEE Trans Circ Syst Video Technol 16(2):280–285

    Article  Google Scholar 

  34. Stark JA (2000) Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Trans Image Process 9(5):889–896

    Article  Google Scholar 

  35. Tan RT (2008) Visibility in bad weather from a single image. In: IEEE computer society conference on computer vision and pattern recognition (CVPR), pp 1–8

  36. Tan T, Ma R, Winslett M, Yang Y, Yong Y, Zhang Z (2013) Resa: realtime elastic streaming analytics in the cloud. In: ACM Sigmod international conference on management of data, pp 1287–1288. https://dl.acm.org/citation.cfm?id=2465343&CFID=1017797602&CFTOKEN=67128231

  37. Tan H, He X, Wang Z, Liu G (2016) Parallel implementation and optimization of high definition video real-time dehazing. Multimed Tools Appl 76(22):23413–23434

    Article  Google Scholar 

  38. Tang K, Yang J, Wang J (2014) Investigating haze-relevant features in a learning framework for image dehazing. In: IEEE computer society conference on computer vision and pattern recognition (CVPR), pp 2995–3002

  39. Tarel JP, Hautiere N (2009) Fast visibility restoration from a single color or gray level image. In: IEEE international conference on computer vision (ICCV), vol 30, issue 2, pp 2201–2208

  40. Toshniwal A, Taneja S, Shukla A, Ramasamy K, Patel JM et al (2014) Storm@twitter. In: ACM Sigmod international conference on management of data, pp 147–156

  41. Treibitz T, Schechner YY (2009) Active polarization descattering. IEEE Trans Pattern Anal Mach Intell (PAMI) 31(3):385–399

    Article  Google Scholar 

  42. Weishan Z, Pengcheng D, Xin L (2014) A realtime framework for video object detection with Storm. In: Conference on ubiquitous intelligence and computing, pp 732–737. http://dl.acm.org/citation.cfm?id=2763957

  43. Wu J, Bisio I, Gniady C, Hossain E, Valla M, Li H (2014) Context-aware network and communications: part 1. IEEE Commun Mag 52(6):14–15

    Article  Google Scholar 

  44. Wu J, Guo S, Li J, Zeng D (2016) Big data meet green challenges: greening big data. IEEE Syst J 10(3):873–887

    Article  Google Scholar 

  45. Xiao C, Gan J (2012) Fast image dehazing using guided joint bilateral filter. Vis Comput 28(6):713–721

    Article  Google Scholar 

  46. Yu J, Xiao C, Li D (2010) Physics-based fast single image fog removal. In: IEEE international conference on signal processing (ICSP), pp 1048–1052

  47. Zhang W, Hou X (2017) Light source point cluster selection-based atmospheric light estimation. Multimed Tools Appl (11):1–12. https://link.springer.com/article/10.1007/s11042-017-4547-7

  48. Zhang J, Li L, Zhang Y, Yang G, Cao X, Sun J (2011) Video dehazing with spatial and temporal coherence. Vis Comput 27(6-8):749–757

    Article  Google Scholar 

  49. Zhang W, Xu L, Li Z, Liu Y (2016) A deep-intelligence framework for online video processing. IEEE Softw 32(2):44–51

    Article  Google Scholar 

  50. Zhang J, Cao Y, Fnag S, Y Kang, Chen CW (2017) Fast haze removal for nighttime image using maximum reflectance prior. In: Conference on computer vision and pattern recognition (CVPR)

  51. Zhu Q, Mai J, Shao L (2015) A fast single image haze removal using color attenuation prior. IEEE Trans Image Process (TIP) 24(11):3522–3533

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work is financially supported by National Natural Science Foundation of China (61202269, 61472089, 61202293, 31600591), Science and Technology Plan Project of Guangdong Province (2014A0050503057, 2015A020209124, 2016A020210087).

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Authors and Affiliations

  1. College of Mathematics and Informatics, South China Agricultural University, Guangdong Sheng, China

    Meihua Wang, Jiaming Mai & Yun Liang

  2. School of Computer Science and Technology, Guangdong University of Technology, Guangdong, China

    Ruichu Cai

  3. Advanced Digital Sciences Center, Illinois at Singapore Pte.Ltd., Singapore, Singapore

    Tom Zhengjia Fu & Zhenjie Zhang

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  1. Meihua Wang
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  2. Jiaming Mai
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  3. Yun Liang
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  4. Ruichu Cai
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  5. Tom Zhengjia Fu
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  6. Zhenjie Zhang
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Correspondence to Jiaming Mai.

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Wang, M., Mai, J., Liang, Y. et al. A component-driven distributed framework for real-time video dehazing. Multimed Tools Appl 77, 11259–11276 (2018). https://doi.org/10.1007/s11042-017-5518-8

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  • DOI: https://doi.org/10.1007/s11042-017-5518-8

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