Bilateral filter-based adaptive nonuniformity correction for infrared focal-plane array systems

Rossi, Alessandro; Diani, Marco; Corsini, Giovanni

doi:10.1117/1.3425660

Cited by 32 publications

(27 citation statements)

References 16 publications

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“…One is the gated adaptive LMS algorithm with Gaussian filter [8], denoted by GALMS. The other one is LMS algorithm with the bilateral filter [22], denoted by BFLMS. Our algorithm is denoted by FGLMS.…”

Section: Simulation On Images With Simulated Nonuniformitymentioning

confidence: 99%

“…The ''desired'' image is expected to be equal to the true infrared radiance. As the FPN is spatially independent and identically distributed (iid) after the initial Opt Rev (2015) 22:614-622 615 calibration, spatial low-pass filters can be applied to the corrected frames to produce a suitable ''desired'' image [8,9,21,22]. …”

Section: Traditional Sense-based Nuc Algorithmsmentioning

confidence: 99%

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A scene-based nonuniformity correction algorithm based on fuzzy logic

Huang

Fan

et al. 2015

Opt Rev

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Scene-based nonuniformity correction algorithms based on the LMS adaptive filter are quite efficient to reduce the fixed pattern noise in infrared images. They are famous for their low cost of computation and storage recourses. Unfortunately, ghosting artifacts can be easily introduced in edge areas when the inter-frame motion slows. In this paper, a gated scene-based nonuniformity correction algorithm is proposed. A novel low-pass filter based on the fuzzy logic is proposed to estimate the true scene radiation as the desired signal in the LMS adaptive filter. The fuzzy logic can also evaluate the probability that a pixel and its locals belong to edge areas. Then the update of the correction parameters for the pixels in edge areas can be gated. The experiment results show that our method is reliable and the ghosting artifacts are reduced.

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Section: Simulation On Images With Simulated Nonuniformitymentioning

confidence: 99%

Section: Traditional Sense-based Nuc Algorithmsmentioning

confidence: 99%

A scene-based nonuniformity correction algorithm based on fuzzy logic

Huang

Fan

et al. 2015

Opt Rev

View full text Add to dashboard Cite

show abstract

“…12,13 The introduction of the BF is very effective to obtain reliable target estimates in proximity of regions of the scene characterized by strong edges. The BF replaces each sample of the processed image with a weighted average of its neighbours.…”

Section: Bilateral-filter (Bf) Deghostingmentioning

confidence: 99%

“…The former is based on the employment of an edge-preserving spatial filter. 12,13 The latter relies on the computation of the temporal statistics of the error signal in the Scribner's algorithm. 14 In this work, a comparison of the performance of the mentioned deghosting techniques has been carried out.…”

Section: Introductionmentioning

confidence: 99%

A comparison of deghosting techniques in adaptive nonuniformity correction for IR focal-plane array systems

Rossi

Diani

Corsini

2010

Electro-Optical and Infrared Systems: Technology and Applications VII

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Focal-plane array (FPA) IR systems are affected by fixed-pattern noise (FPN) which is caused by the nonuniformity of the responses of the detectors that compose the array. Due to the slow temporal drift of FPN, several scene-based nonuniformity correction (NUC) techniques have been developed that operate calibration during the acquisition only by means of the collected data. Unfortunately, such algorithms are affected by a collateral damaging problem: ghosting-like artifacts are generated by the edges in the scene and appear as a reverse image in the original position. In this paper, we compare the performance of representative methods for reducing ghosting. Such methods relate to the least mean square (LMS)-based NUC algorithm proposed by D.A. Scribner. In particular, attention is focused on a recently proposed technique which is based on the computation of the temporal statistics of the error signal in the aforementioned LMS-NUC algorithm. In this work, the performances of the deghosting techniques have been investigated by means of IR data corrupted with simulated nonuniformity noise over the detectors of the FPA. Finally, we have made some considerations on the computational aspect which is a challenging task for the employment of such techniques in real-time systems.

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“…To solve this problem, two main categories of nonuniformity correction (NUC), i.e., calibrationbased (CB) methods [2]- [5] and scene-based (SB) methods [6]- [16], have been developed in recent years. CB methods have lower computational complexity but rely on calibrating the IRFPA at distinct temperatures which consume lots of additional infrared resources and interrupt normal imaging process; SB methods are adapted to the time-drift of nonuniformity response, but their higher computational complexity make the real-time processing hard to achieve, and a new problem, also known as ghosting artifacts, is brought to the infrared image.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Image-Registration-Based Nonuniformity Correction Algorithm With Ghost Artifacts Eliminating for Infrared Focal Plane Arrays

2015

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In this paper, we present a new adaptive image registration nonuniformity correction method with the function of eliminating ghost artifacts. This method assumes that the irradiation of objects stays unchanged during the adjacent two frames' time interval and then corrects the corresponding pixels of two frames by the result of image registration. With regard to real-time continuous image sequence, we first calculate the displacement vectors based on their row and column projections. Then, by bidirectional image registration, we can get the overlapped area matrices of two frames accurately. Meanwhile, a variance threshold is set to judge the scene classification, and then, displacement revising is selectively added to decrease stripe noise. Considering that moving targets exist, the error function for updating is also accordingly adapted to eliminate the ghost artifacts. By using the least-mean-square-error iteration algorithm, the gain and offset coefficients of the overlapped area can be updated in real time with the image sequence adaptively. The advantages of this algorithm lie in its high efficiency of image processing, low computational complexity, and few ghost artifacts. A clean infrared image sequence and two real infrared datasets with nonuniformity are used to compare the ability and correction performance of different algorithms. The results show that our algorithm performs better than other compared algorithms and obtains almost no ghost artifacts.

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Bilateral filter-based adaptive nonuniformity correction for infrared focal-plane array systems

Cited by 32 publications

References 16 publications

A scene-based nonuniformity correction algorithm based on fuzzy logic

A scene-based nonuniformity correction algorithm based on fuzzy logic

A comparison of deghosting techniques in adaptive nonuniformity correction for IR focal-plane array systems

Adaptive Image-Registration-Based Nonuniformity Correction Algorithm With Ghost Artifacts Eliminating for Infrared Focal Plane Arrays

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