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昆明物理研究所 昆明,650223
收稿日期:2016-01-11,
修回日期:2016-03-04,
纸质出版日期:2016-06-25
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洪闻青, 姚立斌, 姬荣斌等. 基于不同积分时间帧累加的红外图像超帧方法[J]. 光学精密工程, 2016,24(6): 1490-1500
HONG Wen-qing, YAO Li-bin, JI Rong-bin etc. A super-frame processing method for infrared image based on accumulation of different integration time frame[J]. Editorial Office of Optics and Precision Engineering, 2016,24(6): 1490-1500
洪闻青, 姚立斌, 姬荣斌等. 基于不同积分时间帧累加的红外图像超帧方法[J]. 光学精密工程, 2016,24(6): 1490-1500 DOI: 10.3788/OPE.20162406.1490.
HONG Wen-qing, YAO Li-bin, JI Rong-bin etc. A super-frame processing method for infrared image based on accumulation of different integration time frame[J]. Editorial Office of Optics and Precision Engineering, 2016,24(6): 1490-1500 DOI: 10.3788/OPE.20162406.1490.
针对大多数常规红外成像系统单帧成帧时间内探测器组件响应动态范围有限,以及超帧算法需要借助其他复杂装置或专用电路的不足,提出了一种基于不同积分时间帧累加的红外图像超帧处理方法,采用电子学处理方法对整个超帧处理过程进行了研究。分析了限制红外探测器响应动态范围的原因,简单介绍了帧积分方法的原理和利弊。然后对不同积分时间下获得的图像进行了非均匀性校正、帧信息融合和新帧映射。实验结果表明:本文方法提高了系统的噪声等效温差(NETD),捕获了更多的场景原始图像信息,丰富了图像的灰度层次,增加了图像的信息熵。该方法能够等效拓展探测器的响应动态范围,增加场景原始信息的捕获,提高成像系统的输出信号信噪比以及探测灵敏度。
Since the dynamic response range of the detector component within the period of single framing for most regular infrared imaging system is limited
and the super-frame calculation can not be conducted without the help of other complicated devices or dedicated circuits
a method based on accumulation of different integration time frame for infrared image super-framing was put forward. In this method
a research was conducted on the whole super-framing process by means of electronic method
the reason for limited dynamic response range of the infrared detector was analyzed
and the principle
advantages and disadvantages of the frame integration method was introduced. Then non-uniform correction
frame information integration and new frame mapping were conducted on images obtained under different integration time. It is showed in the test that the method helps to improve the NETD of the system
capture more original image information
enrich the gray level of the image
and increase the image information entropy. By using this method
the dynamic response range of the detector can be expanded
more original scene information can be captured
and the detection sensitivity and signal to noise ratio of the image output signal can be improved.
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