首页> 外文会议>Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE >Modelling, calibration and correction of nonlinear illumination dependent fixed pattern noise in logarithmic CMOS image sensors
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Modelling, calibration and correction of nonlinear illumination dependent fixed pattern noise in logarithmic CMOS image sensors

机译:对数CMOS图像传感器中与非线性照明有关的固定模式噪声的建模,校准和校正

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At present, most CMOS image sensors use an array of pixels with a linear response. However, logarithmic CMOS sensors are also possible, which are capable of imaging high dynamic range scenes without saturating. Unfortunately, logarithmic sensors suffer from fixed pattern noise (FPN). Work reported in the literature generally assumes the FPN is independent of illumination. This paper develops a nonlinear model y=a+bln(c+x) of the pixel response y to an illuminance z showing that FPN arises from variation of the offset a, gain b and bias c. Equations are derived which can be used to extract these parameters by calibration against a uniform illuminance of varying intensity. Experimental results, demonstrating parameter calibration and FPN correction, show that the nonlinear model outperforms outputs previous models that assume either only offset or offset and gain variation.
机译:当前,大多数CMOS图像传感器使用具有线性响应的像素阵列。但是,对数CMOS传感器也是可能的,它能够在不饱和的情况下对高动态范围场景进行成像。不幸的是,对数传感器遭受固定模式噪声(FPN)的困扰。文献中报道的工作通常假定FPN与照明无关。本文建立了像素模型y对照度z的非线性模型y = a + bln(c + x),表明FPN是由偏移量a,增益b和偏置c的变化引起的。推导出方程,该方程可用于通过针对变化强度的均匀照度进行校准来提取这些参数。实验结果表明参数校准和FPN校正,表明非线性模型的性能优于以前假设仅存在偏移或存在偏移和增益变化的模型。

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