Scene-based nonuniformity correction for airborne point target detection systems

Abstract

Images acquired by airborne infrared search and track (IRST) systems are often characterized by nonuniform noise. In this paper, a scene-based nonuniformity correction method for infrared focal-plane arrays (FPAs) is proposed based on the constant statistics of the received radiation ratios of adjacent pixels. The gain of each pixel is computed recursively based on the ratios between adjacent pixels, which are estimated through a median operation. Then, an elaborate mathematical model describing the error propagation, derived from random noise and the recursive calculation procedure, is established. The proposed method maintains the characteristics of traditional methods in calibrating the whole electro-optics chain, in compensating for temporal drifts, and in not preserving the radiometric accuracy of the system. Moreover, the proposed method is robust since the frame number is the only variant, and is suitable for real-time applications owing to its low computational complexity and simplicity of implementation. The experimental results, on different scenes from a proof-of-concept point target detection system with a long-wave Sofradir FPA, demonstrate the compelling performance of the proposed method.

Temporal-Spatial Nonlinear Filtering for Infrared Focal Plane Array Stripe Nonuniformity Correction

“…Hardie et al [16] applied an adaptive threshold to update statistical parameter estimate in CS-NUC. Zhou et al [17] proposed a multi-frame statistics based nonuniformity correction method for airborne infrared imaging systems. Afterward, the registration-based methods were proposed, and they assume that the response of each detector to the same scene is identical and the difference is on account of the nonuniformity.…”

“…Finally, the nonuniformity can be obtained via Equation (17) and the n-th frame of the corrected image, which is denoted as X n c (p) can be calculated as follows:…”

Single Infrared Image-Based Stripe Nonuniformity Correction via a Two-Stage Filtering Method

“…More temperature segmentations can produce more accurate correction results [6]. In the second class, several typical strategies have been used such as the constant statistics methods [1,8], the filtering estimation methods [9,10], the image registration methods [11,12] and so on. Generally, these scene-based NUC approaches seek to make a reasonable estimate for model parameters, based on the FPN’s time-invariance.…”

“…In many infrared (IR) sensing applications such as target detection [1] and face recognition [2], one has to process images and videos containing undesirable fixed pattern noise (FPN) that is caused by the nonuniformity of IR detector response [3,4]. Hence, it is important for IR sensors to correct the nonuniformity and remove the FPN in raw images.…”

Interior Radiation Noise Reduction Method Based on Multiframe Processing in Infrared Focal Plane Arrays Imaging System

“…As a result, they have limited effectiveness in interior radiation noise removal and are susceptible to the scene information. In 2017, Zhou et al proposed a multi-frame statistics based nonuniformity correction method for airborne infrared imaging systems that can effectively compensate the noise in optical systems and detectors [23]. However, such statistics based method inevitably have ghosting artifacts.…”