Enhancing nighttime surveillance video via gradient fusion

This paper presents an effective method to enhance the quality of dim light surveillance via gradient fusion. We simply take the advantage that surveillance cameras capture a large quantity of valuable information at the same viewpoint during the day. And it can be used to make the video at night easier to perceive. Based on a gradient domain technique, all the important local perceptual cues from the original video are automatically combined with the supporting daytime context, while avoiding traditional problems such as aliasing, ghosting and haloing. Experimental results show that our method outperforms the state-of-the-art ones, and can even handle some challenging conditions without altering the parameters.

[1]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[2]  Zeev Farbman,et al.  Convolution pyramids , 2011, ACM Trans. Graph..

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Ramesh Raskar,et al.  Image fusion for context enhancement and video surrealism , 2004, NPAR '04.

[5]  Z. Zivkovic Improved adaptive Gaussian mixture model for background subtraction , 2004, ICPR 2004.

[6]  Ming-Ting Sun,et al.  An effecive night video enhancement algorithm , 2011, 2011 Visual Communications and Image Processing (VCIP).

[7]  Takeo Kanade,et al.  Denighting: Enhancement of nighttime images for a surveillance camera , 2008, 2008 19th International Conference on Pattern Recognition.

[8]  Tieniu Tan,et al.  Context Enhancement of Nighttime Surveillance by Image Fusion , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[9]  Jiangtao Wen,et al.  Fast efficient algorithm for enhancement of low lighting video , 2010, 2011 IEEE International Conference on Multimedia and Expo.