Fixed Pattern Noise Correction for Wide Dynamic Range CMOS Image Sensor with Reinhard Tone Mapping Operator

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