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| Fixed pattern noise is characterised by the same pattern of 'hot' pixels occurring with images taken under the same conditions of temperature and exposure. This problem is often made worse when the sensor is at higher temperatures. | Fixed pattern noise is characterised by the same pattern of 'hot' pixels occurring with images taken under the same conditions of temperature and exposure. This problem is often made worse when the sensor is at higher temperatures. | ||
| The paper describes a method that uses a video sequence to correct gain fixed pattern noise (FPN) in an image sensor. The captured sequence and its optical flow are used to estimate gain FPN. Assuming brightness constancy along the motion trajectories, the pixels are grouped in blocks and the gains of the pixels in each block are estimated by iteratively minimizing the sum of the squared brightness variations along the motion trajectories. Significant reductions in gain FPN are demonstrated using both real and synthetically generated video sequences with modest computations. | |||
| ==References== | ==References== | ||
Revision as of 19:51, 17 December 2007
- For fixed pattern noise in video projectors see Screen door effect.
Fixed pattern noise is the term given to a particular noise pattern on digital imaging sensors often noticeable during longer exposure shots where particular pixels are susceptible to giving brighter intensities above the general background noise.
Fixed pattern noise is characterised by the same pattern of 'hot' pixels occurring with images taken under the same conditions of temperature and exposure. This problem is often made worse when the sensor is at higher temperatures.
The paper describes a method that uses a video sequence to correct gain fixed pattern noise (FPN) in an image sensor. The captured sequence and its optical flow are used to estimate gain FPN. Assuming brightness constancy along the motion trajectories, the pixels are grouped in blocks and the gains of the pixels in each block are estimated by iteratively minimizing the sum of the squared brightness variations along the motion trajectories. Significant reductions in gain FPN are demonstrated using both real and synthetically generated video sequences with modest computations.
References
http://www.cambridgeincolour.com/tutorials/noise.htm
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