| 基于人眼视觉特性的IRFPA非均匀性校正算法研究 |
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| 引用本文： | 代少升,易伟男,聂合文,杨雨.基于人眼视觉特性的IRFPA非均匀性校正算法研究[J].半导体光电,2020,41(1):59-63, 67. |
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| 作者姓名： | 代少升 易伟男 聂合文 杨雨 |
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| 作者单位： | 重庆邮电大学 信号与信息处理重庆市重点实验室, 重庆 400065,重庆邮电大学 信号与信息处理重庆市重点实验室, 重庆 400065,重庆邮电大学 信号与信息处理重庆市重点实验室, 重庆 400065,重庆邮电大学 信号与信息处理重庆市重点实验室, 重庆 400065 |
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| 摘 要： | 红外焦平面器件普遍存在着非均匀性问题,对红外焦平面阵列(IRFPA)实施非均匀性校正对提高成像质量具有重要意义。传统的IRFPA多点校正算法存在运算量大、实时性能低、实用效果差等问题,为此文章综合人眼视觉特性,提出IRFPA非均匀性多点校正算法。人眼视觉对图像的灰度分辨能力是有阈值限制的,利用这种分辨阈值可以对IRFPA的标定点进行有效压缩,生成像元号-校正系数表,然后通过查找系数表,实现IRFPA的非均匀性实时压缩校正。实验证明,提出的IRFPA非均匀性校正算法较传统的IRFPA非均匀性校正算法实时性能更好,非均匀性降低了0.203%。
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| 关 键 词： | IRFPA 非均匀性校正 人眼视觉特性 多点校正 DSP |
| 收稿时间： | 2019/11/23 0:00:00 |
Research on IRFPA Non-uniformity Correction Algorithm Based on Human Visual Characteristics |
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| DAI Shaosheng,YI Weinan,NIE Hewen and YANG Yu.Research on IRFPA Non-uniformity Correction Algorithm Based on Human Visual Characteristics[J].Semiconductor Optoelectronics,2020,41(1):59-63, 67. |
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| Authors: | DAI Shaosheng YI Weinan NIE Hewen and YANG Yu |
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| Affiliation: | Chongqing Key Lab. of Signal and Information Processing, Chongqing University of Posts and Telecommun., Chongqing 400065, CHN,Chongqing Key Lab. of Signal and Information Processing, Chongqing University of Posts and Telecommun., Chongqing 400065, CHN,Chongqing Key Lab. of Signal and Information Processing, Chongqing University of Posts and Telecommun., Chongqing 400065, CHN and Chongqing Key Lab. of Signal and Information Processing, Chongqing University of Posts and Telecommun., Chongqing 400065, CHN |
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| Abstract: | Infrared focal plane devices generally present non-uniformity problems, and implementing non-uniformity correction on IRFPA is of great significance for improving image quality. The traditional IRFPA multi-point correction algorithm is of such problems as large amount of computation, low real-time performance and poor practical effect. Therefore, combining with the human visual characteristics, a multi-point correction method is proposed for IRFPA non-uniformity. The human eye vision has a threshold limitation on the gray resolution capability of the image, and with this resolution threshold, the calibration point of the IRFPA can be effectively compressed to generate a pixel number-correction coefficient table. Then, the IRFPA non-uniformity real-time compression correction can be implemented by looking up the coefficient table. The experimental results show that the proposed algorithm has better real-time performance than traditional algorithms, and the non-uniformity is reduced by 0.203%. |
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| Keywords: | IRFPA non-uniformity correction human visual characteristics multi-point correction DSP |
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