Scene-based Nonuniformity Correction Algorithms Research Articles

A New Scene-Based Non-Uniformity Correction Algorithm for Infrared Focal Plane Array

Non-uniformity exists in all IRFPA detectors. A new scene-based algorithm is developed to compensate for bias non-uniformity in focal-plane arrays. The technique is based on use of estimates of interframe sub-pixel shifts in an image sequence, in conjunction with a linear interpolation model for the motion, to exact information on the bias non-uniformity algebraically. Through a serial of experiment on real IRFPA images, we find the algorithm is effective and is more promising in comparison with the statistical approaches.

Generalized algebraic scene-based nonuniformity correction algorithm

A generalization of a recently developed algebraic scene-based nonuniformity correction algorithm for focal plane array (FPA) sensors is presented. The new technique uses pairs of image frames exhibiting arbitrary one- or two-dimensional translational motion to compute compensator quantities that are then used to remove nonuniformity in the bias of the FPA response. Unlike its predecessor, the generalization does not require the use of either a blackbody calibration target or a shutter. The algorithm has a low computational overhead, lending itself to real-time hardware implementation. The high-quality correction ability of this technique is demonstrated through application to real IR data from both cooled and uncooled infrared FPAs. A theoretical and experimental error analysis is performed to study the accuracy of the bias compensator estimates in the presence of two main sources of error.

Radiometrically accurate scene-based nonuniformity correction for array sensors.

A novel radiometrically accurate scene-based nonuniformity correction (NUC) algorithm is described. The technique combines absolute calibration with a recently reported algebraic scene-based NUC algorithm. The technique is based on the following principle: First, detectors that are along the perimeter of the focal-plane array are absolutely calibrated; then the calibration is transported to the remaining uncalibrated interior detectors through the application of the algebraic scene-based algorithm, which utilizes pairs of image frames exhibiting arbitrary global motion. The key advantage of this technique is that it can obtain radiometric accuracy during NUC without disrupting camera operation. Accurate estimates of the bias nonuniformity can be achieved with relatively few frames, which can be fewer than ten frame pairs. Advantages of this technique are discussed, and a thorough performance analysis is presented with use of simulated and real infrared imagery.

Scene-based nonuniformity correction with video sequences and registration

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance (or true scene value). These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and the corresponding observed values through a given detector, a curve-fitting procedure is used to estimate the individual detector response parameters. These can then be used to correct for detector nonuniformity. The strength of the algorithm lies in its simplicity and low computational complexity. Experimental results, to illustrate the performance of the algorithm, include the use of visible-range imagery with simulated nonuniformity and infrared imagery with real nonuniformity.

Digital implementation of scene-based non-uniformity correction for microscan-mode infrared cameras

A real-time implementation of scene-based non-uniformity correction (SBNUC) using a digital technique is proposed for microscan-mode staring infrared cameras. Most SBNUC algorithms, without sensor motion, cannot be applied to stationary scenes because of image blurring and fading. Using a microscanning effect, coupled with a modified version of Scribner's algorithm, the proposed technique can correct the artefacts and non-uniformities in real-time.

Nonuniformity correction of infrared image sequences using the constant-statistics constraint

Using clues from neurobiological adaptation, we have developed the constant-statistics (CS) algorithm for nonuniformity correction of infrared focal point arrays (IRFPAs) and other imaging arrays. The CS model provides an efficient implementation that can also eliminate much of the ghosting artifact that plagues all scene-based nonuniformity correction (NUC) algorithms. The CS algorithm with deghosting is demonstrated on synthetic and real infrared (IR) sequences and shown to improve the overall accuracy of the correction procedure.