Abstract
Achieving a high fill factor is a bottleneck problem for capturing high-quality images. There are hardware and software solutions to overcome this problem. In the solutions, the fill factor is known. However, this is an industrial secrecy by most image sensor manufacturers due to its direct effect on the assessment of the sensor quality. In this paper, we propose a method to estimate the fill factor of a camera sensor from an arbitrary single image. The virtual response function of the imaging process and sensor irradiance are estimated from the generation of virtual images. Then the global intensity values of the virtual images are obtained, which are the result of fusing the virtual images into a single, high dynamic range radiance map. A non-linear function is inferred from the original and global intensity values of the virtual images. The fill factor is estimated by the conditional minimum of the inferred function. The method is verified using images of two datasets. The results show that our method estimates the fill factor correctly with significant stability and accuracy from one single arbitrary image according to the low standard deviation of the estimated fill factors from each of images and for each camera.
Highlights
Since the first developed digital camera equipped with charge-coupled device (CCD) image sensors in 1975 [1], the CCD digital camera has played a more and more important role in both normal life and scientific studies
We showed that by assuming a known fill factor ζ j a virtual image Mvij is generated and the sensor irradiance is mapped to the virtual image by a corresponding virtual camera response function (see Equation (7))
We propose a method to estimate the fill factor of a camera sensor from an arbitrary single image
Summary
Since the first developed digital camera equipped with charge-coupled device (CCD) image sensors in 1975 [1], the CCD digital camera has played a more and more important role in both normal life and scientific studies. This popularity is thanks to significant progress over the past decades in digital camera sensory techniques and image processing algorithms; especially achievements in increasing image resolution and improving low-light performance [2]. The progress of achievements are due to the reduction of the sensory element (the pixel size), improving the conversion of collected photons to electrons (the quantum efficiency), and using hardware techniques on the sensor [1,3].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
