Improved interframe registration based nonuniformity correction for focal plane arrays

Zuo, Chao; Chen, Qian; Gu, Guohua; Sui, Xiubao; Ren, Junwen

doi:10.1016/j.infrared.2012.04.002

Cited by 26 publications

(15 citation statements)

References 18 publications

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“…Another SBNUC method is the registration-based approach, which exploits the global motion between frames by considering that each detector in the array should respond identically when observing the same scene point [6,7,8,9,10,11,12,13]. Considering a pure translation motion model for interframe shifts, Ratliff et al [7,8] developed a process that compensates for bias nonuniformity, while Zuo et al [9,10,11] provided both gain and bias correction methods.…”

Section: Introductionmentioning

confidence: 99%

“…Considering a pure translation motion model for interframe shifts, Ratliff et al [7,8] developed a process that compensates for bias nonuniformity, while Zuo et al [9,10,11] provided both gain and bias correction methods. Black et al [12,13], on the other hand, offered an approach to deal with both high- and low-spatial frequency nonuniformity.…”

Section: Introductionmentioning

confidence: 99%

“…This leads us to its main challenge that is assuring reliable registration in practical applications conditions like: highly corrupted frames, the presence of local motion in the scene independent from the global one, and complex motion features between frames rather than pure horizontal and vertical motions. Recently, a lot of research has focused on facing these challenges, and the most relevant to our work is the one conducted by Zuo et al [10] where the authors proposed three strategies to overcome the problems cited above, and these strategies will be discussed in detail in the next section.…”

Section: Introductionmentioning

confidence: 99%

“…We also compare our results with two novel methods from both SBNUC techniques, namely: interframe registration-based NUC (IRNUC) [10] and adaptive SBNUC based on neural network (SBNUC-NN) [17]. …”

Section: Introductionmentioning

confidence: 99%

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Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

Boutemedjet

Deng

Zhao

2016

Sensors

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In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

Boutemedjet

Deng

Zhao

2016

Sensors

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“…[12][13][14] Interframe registration-based LMS method 12,13 first registers the previous corrected image with the current input image by assuming that only slight translational motion exists. Then, this technique minimizes the LMS error between the previously shifted image and the currently corrected image.…”

Section: Introductionmentioning

confidence: 99%

Regularization approach to scene-based nonuniformity correction

Kim

et al. 2014

Opt. Eng

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Abstract. Various scene-based nonuniformity correction (SBNUC) methods have been proposed to diminish the residual nonuniformity (RNU) of the infrared focal plane array (IRFPA) sensors. Most existing SBNUC techniques require a relatively large number of image frames to reduce the RNU. In some applications, however, there is not enough time for capturing a large number of image frames prior to the camera operation, or only several image frames are available to users. A new scene-based approach that can correct the RNU using only several image frames is proposed. The proposed method formulates the SBNUC process as an energy minimization problem. In the proposed energy function, we introduce regularization terms for the parameter regarding the responsivity of the IRFPA as well as for the true scene irradiance. Correction results are obtained by minimizing the energy function using a numerical technique. Experimental results demonstrate the effectiveness of the proposed method. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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A time-domain projection-based registration-scene-based nonuniformity correction technology and its detailed hardware realization

Liu

Qiu

2014

OPT REV

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Improved interframe registration based nonuniformity correction for focal plane arrays

Cited by 26 publications

References 18 publications

Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

Regularization approach to scene-based nonuniformity correction

A time-domain projection-based registration-scene-based nonuniformity correction technology and its detailed hardware realization

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