کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1539817 | 996646 | 2008 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An enhanced non-uniformity correction algorithm for IRFPA based on neural network
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
مواد الکترونیکی، نوری و مغناطیسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Influenced by detector materials' non-uniformity, growth and etching techniques, etc., every detector's responsivity of infrared focal plane arrays (IRFPA) is different, which results in non-uniformity of IRFPA. And non-uniformity of IRFPA generates fixed pattern noises (FPN) that are superposed on infrared image. And it may degrade the infrared image quality, which greatly limits the application of IRFPA. Non-uniformity correction (NUC) is an important technique for IRFPA. The traditional non-uniformity correction algorithm based on neural network and its modified algorithms are analyzed in this paper. And a new improved non-uniformity correction algorithm based on neural network is proposed in this paper. In this algorithm, the desired image is estimated by using three successive images in an infrared sequence. And blurring effect caused by motion is avoided by applying implicit motion detection and edge detection. So the estimation image is closer to real image than the estimation image estimated by other algorithms, which results in fast convergence speed of correction parameters. A comparison is made to these algorithms in this paper. And experimental results show that the algorithm proposed in this paper can correct the non-uniformity of IRFPA effectively and it prevails over other algorithms based on neural network.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optics Communications - Volume 281, Issue 8, 15 April 2008, Pages 2040-2045
Journal: Optics Communications - Volume 281, Issue 8, 15 April 2008, Pages 2040-2045
نویسندگان
BingJian Wang, ShangQian Liu, LiPing Bai,