Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras

• Main Authors: Alejandro Wolf, Jorge E. Pezoa, Miguel Figueroa
• Format: Article
• Language: English
• Published: MDPI AG 2016-07-01
• Series: Sensors
• Subjects: physical sensors; imaging; infrared imaging; image enhancement; noise in imaging systems; image reconstruction techniques
• Online Access: http://www.mdpi.com/1424-8220/16/7/1121

Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent NU correction performance and a root mean square error of less than 0.25 ∘ C, when the array’s temperature varies by approximately 15 ∘ C.