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On-line nonuniformity and temperature compensation of uncooled IRFPAs using embedded digital hardware

机译:使用嵌入式数字硬件在线不均匀性和加工IRFPA的温度补偿

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We present a model and a signal-processing algorithm for compensating the nonuniformity (NU) noise and surrounding temperature self-heating e ects on the response of uncooled microbolometer-based infrared cameras. The model for the NU noise considers pixelwise gain and o set parameters. The representation for the self-heating dynamics of the camera is an autoregressive moving average (ARMA) model for camera's internal temperature. The algorithm performs initially a two-point calibration at a known surrounding temperature. Next, without modifying the NU parameters, we dynamically compensate variations in the camera readout using both estimates of the ARMA model and measurements of the surrounding temperature taken by a simple sensor embedded in the camera. Tested on a CEDIP Jade UC33 camera, our system compensates reference black-body images at 30 degrees Celsius, with a peak error below 1.3 and a mean error below 0.3 degrees Celsius, in scenarios where the room temperature varied up to 14 degrees Celsius. Moreover, the regularity and simplicity of the algorithm enables us to implement it on embedded digital hardware, thereby reducing its cost, size, and power consumption. We implemented the algorithm on a Xilinx XC6SLX45 FPGA using fixed-point arithmetic. The circuit exhibits an arithmetic error of 0.06 degrees compared to a software double-precision implementation. It compensates 320×240-pixel video at up to 1,437 fps and 640×480-pixel video at up to 360 fps, using 1% of the logic resources of the FPGA, and less than 1 mW of dynamic power at 110 MHz. Adding Gigabit Ethernet communication, HDMI display, and a pseudocolor map on the chip uses 10% of the resources and consumes 915 mW.
机译:我们提出了一个模型,用于在未冷却的基于微测辐射热红外相机的响应补偿非均匀性(NU)噪声和周围温度自发热Ë学分的信号处理算法。对于NU模型噪声考虑按像素增益和邻集的参数。用于照相机的自加热动力学的表示是自回归移动平均(ARMA),用于相机的内部温度模型。该算法最初执行在已知周围温度的两点校准。接着,无需修改NU参数,我们动态地在相机的读出用ARMA模型和通过嵌入在相机的简单传感器拍摄的周围的温度的测量值的两个估计补偿变化。测试了CEDIP玉UC33相机上,我们的系统补偿在30摄氏度的参考黑体图像,具有低于1.3的峰值误差和低于0.3摄氏度的平均误差,在室温变化到14摄氏度的情景。此外,该算法的规律和简单使我们能够实现它在嵌入式数字硬件,从而降低它的成本,尺寸和功耗。我们使用定点运算来实现在Xilinx FPGA XC6SLX45算法。的电路表现出0.06度的算术误差相比,软件双精度实现。它补偿在高达1437 fps的320×240像素的视频,并在高达360 fps的640×480像素的视频,使用FPGA的逻辑资源的1%,并在110 MHz的动态功率小于1mW。添加千兆以太网通信,HDMI显示器,以及芯片上的伪彩图使用的资源的10%,并且消耗915毫瓦。

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