Efficient and accurate conversion-gain estimation of a photon-counting image sensor based on the maximum likelihood estimation

Abstract

We establish a method for estimating conversion gains of image sensors on the basis of a maximum likelihood estimation, one of the most common and well-established statistical approaches. A numerical simulation indicates the proposed method can evaluate the conversion gain more accurately with less data accumulation than known approaches. We also applied this method to experimental images accumulated under a photon-counting–regime illumination condition by a CMOS image sensor that can distinguish how many photoelectrons are generated in each pixel. Resultantly, the conversion gains were determined with an accuracy of three digits from 1000 observed images, whose number is at most 10 times smaller than that required for achieving a similar accuracy by known gain-estimation methods.