Proceedings Article | 12 December 2018
KEYWORDS: Infrared radiation, Infrared detectors, Infrared imaging, Sensors, Infrared sensors, Image filtering, Imaging systems, Nonlinear filtering, Signal processing, Optical filters
Infrared focal plane detectors play very important roles in the field of military optoelectronic imaging. It has shown unique features in national defense and the national economy, but in the manufacture of infrared focal plane imaging detectors, due to the error in the production process, there are inevitably non-uniform response among the pixels, and some blind pixels that completely lose detecting capabilities will generate the fixed pattern noise in the accessed infrared image. In addition, some flicker pixels whose response values changed violently with time, may affect the imaging quality seriously. How to correct image defects caused by these blind pixels is an important topic in the infrared image processing researches. This paper analyzes the causes of the inhomogeneity of the infrared detector's response and the characteristics of the infrared image, then introduces some popular methods about blind pixels detection and compensation for the infrared detector. The traditional alternative kinds of blind pixels compensation methods often calculate the digital number (DN) value from the neighboring pixel response around the blind pixel position using the single frame image and substitute for the corresponding blind pixels response. However, these methods may lead to a single point of high noise in some specific scenarios. Aiming at such faults, an improved real-time blind pixel compensation method is proposed in the paper. We divide blind pixels into dead pixels and flicker pixels firstly according to the pre-calibrating results using blackbodies. Different algorithms with different thresholds are adopted to detect different types of blind pixels. For the dead pixels, the traditional method is used to replace their responses with their neighboring pixels. For the flicker pixels, a queue consisting of a series of image sequences is built in the memory, temporal filtering is performed for the input image series to reduce the time domain noise. Especially for flicker pixels with contiguous slices, it can better smooth the non-linear error caused by the sharp transition of pixel response with time. For blind pixels on the current frame image, their DN values are replaced by the previous frame sliding filter result in the image sequence queue. In order to simplify the complexity of the hardware design, the temporal upper threshold in the time domain filtering is also set. If the temporal filtering time reaches the upper threshold, the value matching conditions are still not found to compensate for the blind pixels, then the traditional alternative method is used to fill in to ensure the processing time limitation. The algorithm mentioned above and the calculation complexity of hardware implementation are given in detail. Afterwards, the platform for hardware system and the blind pixel correction method described via Verilog HDL and realized on this hardware platform are illustrated. The experimental results show that the algorithm can effectively compensate for the influence of blind pixels on the basis of real-time performance, and plays an important role in the improvement of image quality
