Ghosting reduction in adaptive nonuniformity correction of infrared focal-plane array image sequences

Vera, Rodrigo; Torres, I.S.

doi:10.1109/icip.2003.1246853

Cited by 9 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…9,10 The ALR method handles the problem of ghosting-like artifacts introducing an ALR as shown in the following equation Scribner's algorithm with =10 −2 by varying the spatial filter: moving average ͓7 ϫ 7 pixels͔ ͑b͒, ͑c͒…”

Section: Bf Deghosting Resultsmentioning

confidence: 99%

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

2010

View full text Add to dashboard Cite

In scene-based nonuniformity correction (NUC) methods for infrared focal-plane array cameras, the problem of ghosting artifacts widely affects the sensitivity of the imaging system and visibly decreases the image quality. Ghosting artifacts can also degrade the performance of several applications, such as target detection and tracking. We carried out a detailed analysis of the problem using a well-established NUC technique: the least mean square Scribner's algorithm. In order to solve some drawbacks of the original Scribner's algorithm, we introduced in the scheme a new technique that mitigates ghosting. Such technique relies on the employment of an edge-preserving spatial filter for the purpose of computing reliable spatial estimates. We tested the effectiveness of the new technique applying the improved NUC method to an experimental IR sequence of frames acquired in the laboratory. Finally, the performance of the proposed method was discussed and compared to that yielded by a well-established deghosting technique. c 2010 Society of Photo-Optical Instrumentation Engineers. [DOI:10.1117/1.3425660

show abstract

Section: Bf Deghosting Resultsmentioning

confidence: 99%

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

2010

View full text Add to dashboard Cite

show abstract

“…The benefits of the Scribner's algorithm, enhanced with the bilateral filter, have been shown by the visualization of the corrected frames extracted from the processed sequence. The global accuracy of the restored images is measured through the peak signal-to-noise ratio (PSNR), which is widely used in image processing literature to quantify the difference between two images, 11 and is defined as: 10 log 20 (10) where p is the largest value that a pixel can assume (in our case, 1 2 14 − = p for 14-bit images) and RMSE is the root mean square error obtained from the difference between two images. The PSNR is expressed in decibel units (dB) and is herein used to measure the difference between the previously calibrated image and the restored one coming out from the NUC system.…”

Section: Resultsmentioning

confidence: 99%

“…Such parameter is responsible of the convergence of the algorithm and its value has to be carefully set: high values of η make the convergence faster while small values can assure better stability. 10,11 It is important to notice that the computation of the correction parameters strongly depends on the acquired scene and on the spatial filter employed (see equation (3)). …”

Section: Scribner's Algorithmmentioning

confidence: 99%

“…Harris and Chiang 9 improved the Constant Statistics halting the correction in case of insufficient global motion. Vera and Torres 10,11 approached deghosting proposing an enhanced version of the Scribner's algorithm based on adapting the learning-rate to the acquired scene. Finally, Zhang and Shi 12 presented a deghosting technique where the correction coefficients are updated on the basis of the information related to the edges of the scene.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A technique for ghosting artifacts removal in scene-based methods for non-uniformity correction in IR systems

2009

View full text Add to dashboard Cite

In this work we analyze the problem of the ghosting artifacts coming out from non-uniformity correction (NUC) in infrared focal-plane array (IRFPA) imaging systems. We have employed a well-established least mean square (LMS)-based NUC technique which was first introduced by D.A. Scribner. Slow global motion and edges in the scene are the main responsible of the generated ghosting artifacts that can be very damaging especially in target detection and tracking applications. To mitigate the effects of ghosting we propose to replace the linear spatial filter of the analyzed NUC scheme with a non-linear one, known in the literature as bilateral filter, which is able to preserve edges. The proposed technique has been evaluated over an infrared (IR) image sequence with simulated fixed-pattern noise (FPN). A detailed analysis of the results has shown the advantages of the novel deghosting method in terms of accuracy of the calibration and quality of the corrected frames

show abstract

“…6-8 Vera and Torres proposed an enhanced version of the Scribner's algorithm based on an adaptively updated learningrate. 9,10 In 2006, Zhang and Shi presented a deghosting technique where the correction coefficients were updated on the basis of the information related to the edges of the scene. 11 Finally, in 2009 two other deghosting solutions have been proposed.…”

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

View full text Add to dashboard Cite

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.

show abstract

Ghosting reduction in adaptive nonuniformity correction of infrared focal-plane array image sequences

Cited by 9 publications

References 6 publications

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

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

A technique for ghosting artifacts removal in scene-based methods for non-uniformity correction in IR systems

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

Contact Info

Product

Resources

About