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This paper presents a model that is then simplified to explain the temperature dependence of fixed pattern noise (FPN) in logarithmic complementary metal-oxide semiconductor (CMOS) image sensors. The simplified model uses the average dark response of pixels, which depends only on temperature, to help predict the FPN in the light response, which depends on temperature and illuminance. To calibrate a logarithmic camera, one requires images that are taken at different temperatures and illuminances, which need not be measured, of a uniform stimulus. To correct the FPN in an arbitrary image, one uses the simplified model parameters, which are estimated once by the calibration, and the average dark response, which is infrequently determined by closing the aperture. Through simulation (using mismatch data from a real CMOS process) and experiment (using a commercial logarithmic camera), an improvement is shown in the residual error per image, after calibration, when the proposed method is compared with a related method in the literature that does not account for temperature dependence.