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A novel approach for denoising and enhancement of extremely low light video

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Final Year IEEE Projects for BE, B.Tech, ME, M.Tech,M.Sc, MCA & Diploma Students latest Java, .Net, Matlab, NS2, Android, Embedded,Mechanical, Robtics, VLSI, Power Electronics, IEEE projects are given absolutely complete working product and document providing with real time Software & Embedded training......

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A novel approach for denoising and enhancement of extremely low light video

  1. 1. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com A NOVEL APPROACH FOR DENOISING AND ENHANCEMENT OF EXTREMELY LOW-LIGHT VIDEO By A PROJECT REPORT Submitted to the Department of electronics &communication Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY In partial fulfillment of the requirements for the award of the degree Of MASTER OF TECHNOLOGY IN ELECTRONICS &COMMUNICATION ENGINEERING APRIL 2016
  2. 2. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CERTIFICATE Certified that this project report titled “A Novel Approach for Denoising and Enhancement of Extremely Low-light Video” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate. Signature of the Guide Signature of the H.O.D Name Name
  3. 3. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com DECLARATION I hereby declare that the project work entitled “A Novel Approach for Denoising and Enhancement of Extremely Low-light Video” Submitted to BHARATHIDASAN UNIVERSITY in partial fulfillment of the requirement for the award of the Degree of MASTER OF APPLIED ELECTRONICS is a record of original work done by me the guidance of Prof.A.Vinayagam M.Sc., M.Phil., M.E., to the best of my knowledge, the work reported here is not a part of any other thesis or work on the basis of which a degree or award was conferred on an earlier occasion to me or any other candidate. (Student Name) (Reg.No) Place: Date:
  4. 4. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ACKNOWLEDGEMENT I am extremely glad to present my project “A Novel Approach for Denoising and Enhancement of Extremely Low-light Video” which is a part of my curriculum of third semester Master of Science in Computer science. I take this opportunity to express my sincere gratitude to those who helped me in bringing out this project work. I would like to express my Director,Dr. K. ANANDAN, M.A.(Eco.), M.Ed., M.Phil.,(Edn.), PGDCA., CGT., M.A.(Psy.)of who had given me an opportunity to undertake this project. I am highly indebted to Co-OrdinatorProf. Muniappan Department of Physics and thank from my deep heart for her valuable comments I received through my project. I wish to express my deep sense of gratitude to my guide Prof. A.Vinayagam M.Sc., M.Phil., M.E., for her immense help and encouragement for successful completion of this project. I also express my sincere thanks to the all the staff members of Computer science for their kind advice. And last, but not the least, I express my deep gratitude to my parents and friends for their encouragement and support throughout the project.
  5. 5. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ABSTRACT: In this paper, a novel approach for noise reduction and enhancement of extremely low-light video is proposed. For noise removal, a motion adaptive temporal filtering based on a Kalman structured updating is presented. Dynamic range of denoised video is increased by adjustment of RGB histograms using Gamma correction with adaptive clipping thresholds. Finally, residual noise is removed using a nonlocal means (NLM) denoising filter. The proposed method works directly on the color filter array (CFA) raw video for achieving low memory consumption1 .
  6. 6. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com INTRODUCTION: Over the last several decades, there have been substantial improvements in modern digital cameras including resolutions and sensitivity. Despite these improvements, quality of videos in low-light conditions is still limited. Firstly, low-light videos have poor dynamic range. To capture images of high dynamic range, most consumer cameras often rely on automatic exposure control, but longer exposure time results motion blur. Secondly, image sequences captured in low-light conditions often have very low signal-to-noise ratio (SNR). The level of input signal may be modified by increasing sensitivity of cameras. However, noise in an input signal is also amplified with no effective noise reduction steps are taken. Various approaches are developed for enhancing low-light video, Lee et al. proposed a noise-adaptive spatiotemporal filter that considers both Poisson noise and false color noise of input videos. Because their method aims only to videos slightly lower than normal lighting conditions, enhancement of input dynamic range is omitted. Bennett and McMillan developed an enhancement framework for low dynamic range video based on a virtual exposure camera model. Their method includes the bilateral ASTA-filter (Adaptive Spatio-Temporal Accumulation) and tone-mapping with a logarithmic function applied to a large scale and detail features separately. Malm et al. This work was supported by Seoul R&BD Program (WR080951) and in part the STW-KU Research Program. Minjae Kim is with the School of Electrical Engineering, Korea University, Seoul, Korea Dubok Park is with the Department of Visual Information Processing, Korea University, Seoul, Korea David K. Han is with the Office of Naval Research, Arlington, VA, USA Hanseok Ko is with the School of Electrical Engineering, Korea University, Seoul, Korea exploited a 3D structure tensor for adaptive spatio-temporal smoothing, and contrast limited histogram equalization (CLHE) for tone-mapping. Their approach constructs a structureadaptive anisotropic image filter by estimating kernel width of spatial and temporal direction from the second moment matrix of spatio-temporal gradient, so-called “3D structure tensor”. But their method becomes unstable and produces blurry results when illumination level becomes very low because of inaccurate estimation of the anisotropic kernel from input signals with very low SNR. Wang et al. presented an adaptive spatio-temporal connective filter and an adaptive piecewise mapping function for enhancing input videos.
  7. 7. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com They incorporate local image statistics into a bilateral filter to form a noise reduction filter, and applied a piecewise mapping function based on statistical information of the frame segmentation. Since their method was not originally aimed to low-light video enhancement task, some of the steps used, such as optical flow and segmentation, may not provide reliable results with low-light videos. Recently, a threestage processing scheme for denoising and enhancing dark videos was proposed by Xu et al. They utilize a modified version of the well-known nonlocal means (NLM) filter ,for removing noise in an input video before and after tone-mapping by a logarithmic mapping function. Because the 3D NLM filter extended for video denoising requires large computations for finding similar neighbor patch images, the computational cost of their method is relatively high. More recently, new approaches applying the concept of a single image de- hazing algorithm on the intensity inverted low-light video were presented by Dong et al. and Zhang et al. These methods are developed under an observation that statistics of an intensity inverted low- light video are similar to those of a hazy video. However, the estimation of a transmission term in the hazy image acquisition model by using a dark channel prior (DCP) becomes unreliable in very low-light conditions and requires large computation loads. Fig. 1. Example of a moderately low-light video (left) and an extremely low-light video (right) Most of the approaches introduced so far consider only videos under moderately dark conditions in which most objects and background are almost visually recognizable as in Fig. 1. Though, infrared imaging sensors can capture a scene at night time, they provide only gray-level images with low resolutions. Only a few of the approaches provide experimental results for videos in very low-light conditions. When the illumination level is below 0.1 lux, the level of noise becomes relatively much higher than the signal, thus conventional denoising and tone-mapping techniques cannot achieve satisfying enhancement performances. In this paper, the proposed method, which is improved from the previous work is aimed to develop a novel framework to enhance video from extremely low-light environments. It consists of an effective motion adaptive temporal filter based on the Kalman filter framework, a tone- mapping by histogram adjustment with adaptive clipping, and spatial noise reduction with the NLM denoising filter. Since a demosaicing step may cause additional artifacts all steps are implemented to handle the Bayer pattern color filter array (CFA) raw video. The structure of
  8. 8. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com this paper is organized accordingly. Firstly, characteristics of an extremely low-light video are analyzed in Section II. In Section III, detailed procedures of the proposed denoising and enhancing method are described. In Section IV, representative experimental results are provided to assess the performance of proposed method and to compare with the conventional methods. Section V concludes this work and discusses future research.
  9. 9. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CONCLUSION: In this paper, the characteristics of low-light videos captured in an extremely low lighting condition are analyzed, and an effective framework to enhance them is proposed. The proposed framework exploited a motion adaptive temporal filter based on Kalman filter theory and adopted an NLM denoising filter for further smoothing after tone-mapping. The separation of temporal and spatial filters in the proposed noise reduction scheme provides more visually pleasing results than the conventional spatio-temporal filters while preventing ghost effects around moving object regions. An adaptive histogram adjustment using Gamma correction with clipping thresholds is also presented to increase dynamic range of a low-light video. The proposed tone-mapping enhances visibility of a low-light video significantly while maintaining its color balance. Various experimental results indicate that the proposed video enhancement method is highly promising for consumer digital cameras, especially CCTV, black box camera for vehicles, and video signal- based surveillance system.
  10. 10. OUR OFFICES @CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com REFERENCES: [1] S. W. Lee, V. Mail, J. Jang, J. Shin, and J. Paik, “Noise-adaptive spatiotemporal filter for eal- time noise removal in low light level images,”IEEE Trans. Consumer Electron., vol. 51, no. 2, pp. 648-653, May. 2005. [2] E. Bennett and L. McMillan, “Video enhancement using per-pixel virtual exposures,” ACM Trans. Graphics, vol. 24, no. 3, pp. 845-852, Jul. 2005. [3] H. Malm, M. Oskarsson, E. Warrant, P. Clarberg, J. Hasselgren, and C. Lejdfors, “Adaptive enhancement and noise reduction in very low lightlevel video,” In Proc. IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, pp. 1-8, Oct. 2007. [4] Q. Xu, H. Jiang, R. Scopigno, and M. Sbert, “A new approach for very dark video denoising and enhancement,” In Proc. IEEE International Conference on Image Processing, Hong Kong, China, pp. 1185-1188, Sept. 2010. [5] X. Dong, G. Wang, Y. Pang, W. Li, J. Wen, W. Meng, and Y. Lu, “Fast efficient algorithm for enhancement of low lighting video,” In Proc. IEEE International Conference on Multimedia and Expo, Barcelona, Spain, pp. 1-6, Jul. 2011. [6] X. Zhang, P. Shen, L. Luo, L. Zhang, and J. Song, “Enhancement and noise reduction of very low light level images,” In Proc. International Conference on Pattern Recognition, Tsukuba, Japan, pp. 2034-2037, Nov. 2012. [7] M. Kim, D. Park, D. K. Han, and H. Ko, “A novel framework for extremely low-light video enhancement,” in Proc. IEEE International Conference on Consumer Electronics, Las Vegas, USA, pp. 95-96, Jan. 2014. [8] A. Loza, D. Bull, and A. Achim, “Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients,” In Proc. IEEE International Conference on Image Processing, Hong Kong, China, pp. 3553-3556, Sept. 2010.

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