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- W2368846657 abstract "To remove the non-uniformity noise in the infrared image,the denoise and enhancement algorithm based on Kalman filter is proposed.In the framework of Bayesian-MAP inference,the feasibility of Kalman filter was discussed.Due to the inner temperature increment and the circuit parameters' minor changes of the imaging system,each pixel's fixed pattern noise(FPN) varies slowly and non-uniformly between frames.Based on this view,the dark frame was modeled.The level of the FPN was estimated by Kalman filter acted on sequential dark frames.The noise influence factor(NIF) was introduced to evaluate the influence of the FPN to the pixel's output signal.And then,the reasonable weight of each pixel's FPN was determined adaptively by means of NIF.The non-uniformity of the infrared image can be corrected after weighted subtraction FPN from the real noisy image data on pixels one by one.The algorithm was applied in real infrared images and gray mean grads(GMG) was used to evaluate its performance.In target neighborhood,GMG is reduced by 5.1%.It means that the image is smoothed and the edges are preserved well.At the same time,GMG is reduced by 85.5% in smooth neighborhood.The experiments show that algorithm produces an obvious denoise and enhancive effect in both target and smooth regions." @default.
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- W2368846657 date "2012-09-23" @default.
- W2368846657 modified "2023-09-23" @default.
- W2368846657 title "Enhancement algorithm for infrared images based on Kalman filter" @default.
- W2368846657 doi "https://doi.org/10.3785/j.issn.1008-973x.2012.08.027" @default.
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