Fixed pattern noise correction for wide dynamic range CMOS image sensor with Reinhard tone mapping operator

Waqas Mughal, B. Choubey
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引用次数: 8

Abstract

This paper presents an investigation and a correction technique for fixed pattern noise in wide dynamic range image sensor with on the focal plane Reinhard tone mapping. The Human eye is capable of capturing images over a wide dynamic range of illumination; however, typical CMOS image sensors have limited ability to capture dynamic range available in nature. Even when wide dynamic range images are captured, they need to be displayed on conventional media with limited ability to display WDR scenes. Hence, the image has algorithmically transformed by mathematical operators called tone mapping operators to fit the limited dynamic range. In this paper, we report our research on a pixel, which captures a scene with inbuilt tone mapping operator, particularly, the Reinhard photographic mapping operator, which is a monotonically increasing function. However, the inherent Fixed pattern noise(FPN) limits the performance of image sensors. This is mainly due to the variations between the responses of individual pixels within an array of pixels. A simple procedure has been adapted to reduce FPN in which parametric response of the pixel is used, with FPN modeled as variations in the individual parameters. The parameters of each individual pixel are measured, recorded and then used to correct their response.
基于Reinhard色调映射算子的宽动态范围CMOS图像传感器固定模式噪声校正
本文研究了采用焦平面上莱因哈德调映射的宽动态范围图像传感器中固定模式噪声的校正技术。人眼能够在很宽的照明动态范围内捕捉图像;然而,典型的CMOS图像传感器捕捉自然界中可用的动态范围的能力有限。即使捕获了宽动态范围的图像,它们也需要在显示WDR场景的能力有限的传统媒体上显示。因此,图像通过称为色调映射算子的数学算子进行算法变换,以适应有限的动态范围。在本文中,我们报告了用内建的色调映射算子,特别是单调递增函数Reinhard摄影映射算子,来捕捉场景的像素的研究。然而,固有的固定模式噪声(FPN)限制了图像传感器的性能。这主要是由于像素阵列中单个像素的响应之间的变化。采用了一种简单的方法来降低FPN,其中使用像素的参数响应,将FPN建模为单个参数的变化。测量、记录每个像素的参数,然后用来校正它们的响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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