Radiometrically calibrated scene-based nonuniformity correction for infrared array sensors

Ratliff, Bradley M.; Hayat, Majeed M.; Tyo, J. Scott

doi:10.1117/12.450916

Cited by 12 publications

(4 citation statements)

References 12 publications

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“…The statistical techniques model the FPN as a random spatial noise and estimate the statistics of the noise to remove it. [4][5][6][7][8][9] The algebraic techniques, on the other hand, make use of global motion between the frames in the video sequence and attempt to compensate for the nonuniformity by means of algebraic methods without making statistical assumptions about the FPN [10][11][12][13][14][15][16][17][18][19][20][21][22]. The approach proposed in this paper belongs to the second category.…”

Section: Introductionmentioning

confidence: 99%

An Algebraic Nonuniformity Correction Algorithm for Hexagonally-Sampled Infrared Images: A Simulation Study

Sakoğlu

2021

2021 IEEE International Conference on Image Processing (ICIP)

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Infrared imagery, like almost any other two-dimensional (2-D) imagery, have been traditionally sampled and acquired using a rectangular grid. Algebraic fixed-pattern noise/ nonuniformity correction (NUC) algorithms work on this traditional rectangular grid mitigating the most dominant, bias/offset portion of the nonuniformity. On the other hand, it is well-known that hexagonal sampling grid captures more information in sampled data/imagery when compared to traditional rectangular sampling, and a hexagonal addressing scheme for hexagonally-sampled imagery, namely array set addressing scheme, was recently developed. In this work, we derive the bilinear interpolation equations between two image frames for hexagonally-sampled infrared imagery with bias/offset nonuniformity under the 2-D global motion of the scene or the camera, and apply the 2-D algebraic NUC algorithm to hexagonally-sampled imagery. We present a simulation of mid-wave infrared imagery with hexagonallysampled pixel array with bias nonuniformity under simulated global translational motion, and we test the efficiency of the NUC algorithm on the simulated infrared imagery and compare the performance of the hexagonally-sampled pixel array imagery NUC results to those of the traditional rectangularly-sampled pixel array imagery.

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Section: Introductionmentioning

confidence: 99%

An Algebraic Nonuniformity Correction Algorithm for Hexagonally-Sampled Infrared Images: A Simulation Study

Sakoğlu

2021

2021 IEEE International Conference on Image Processing (ICIP)

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“…Existen mecanismos de minimización del error cuadrático que permite encontrar los parámetros de Gain y Offset (ganancia y desplazamiento respectivamente) [8][9][10]. En otro proceso NUC se desarrollan métodos algebraicos [11][12][13] que corrige sólo el Offset, aplicando un análisis geométrico de la radiación sobre las superficies de los detectores. Parte del grupo ha prestado atención a métodos basados en escena usando teoría de estimación [14][15].…”

Section: Introductionunclassified

Corrección de imágenes IR mediante un filtro extendido de estadísticas constantes

Vicencio

Chávez²,

Beltrán

2015

Ingeniare. Rev. chil. ing.

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RESUMENLa calidad de una cámara IR con arreglo en plano focal (IRFPA), en cuanto a la nitidez de imagen, está condicionada al sofisticado proceso de fabricación de su etapa sensora. Es decir, resulta difícil construir foto-detectores con exactamente la misma respuesta de señal eléctrica. Este problema se conoce como "no-uniformidad" en la tecnología IR y se manifiesta como un enrejado superpuesto en la imagen de salida de la cámara, denominado como ruido de patrón fijo (FPN). Este ruido surge debido a que las débiles señales eléctricas de los detectores deben pasar por una etapa amplificadora de alta ganancia, magnificando sus diferencias notoriamente a la salida de la cámara. Con el fin de abordar este problema, el detector se caracteriza como un modelo lineal con dos parámetros (ganancia y desplazamiento). Para encontrar estos parámetros y poder contrarrestar esta desigualdad proponemos un algoritmo basado en un filtro digital no lineal extendido a partir de un desarrollo teórico simple y comprobado experimentalmente, pero consistente, del método estándar de Estadísticas Constantes (CS). Demostramos que el nuevo filtro se compara favorablemente con el CS estándar, en términos de rapidez de convergencia y por consiguiente un pronto desvanecimiento de figuras fantasmas o "ghosting". Se ajustaron los parámetros del algoritmo propuesto y luego fue probado con videos infrarrojos sintetizados y reales, alcanzando elevados niveles de corrección y disminuyendo notoriamente la no uniformidad.Palabras clave: Foto-detectores infrarrojos, plano focal, no-uniformidad, ruido de patrón fijo, figuras fantasmas. ABSTRACTThe quality of an infrared focal plane array camera (IRFPA) in terms of image sharpness is conditioned on the sophisticated manufacturing process of its sensor stage. That is, it is hard to build photo detectors with exactly the same response of electrical signal. This problem is known as "non-uniformity" in IR technology and it manifests itself as superimposed grid in the output image of the camera, termed as fixed pattern noise (FPN). This noise emerges since the weak electric signals from the detectors must undergo a high gain amplifier stage, thus magnifying their differences notoriously at the exit of the camera. To address this problem, the detector is characterized as a linear model with two parameters (gain and offset). To find these parameters and counteract this inequality we propose an algorithm based on a nonlinear digital filter extended from a simple yet consistent experimentally verified theoretical development of the standard method of Constant Statistics (CS). We demonstrate that the new filter compares favorably with CS standard, in terms of convergence speed and therefore prompt fading of ghosting artifact or "ghosting". Parameters of the proposed algorithm were adjusted and when it was tested with synthesized and real infrared video, high levels of correction was achieved, notoriously decreasing the non-uniformity.

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“…We have previously developed a technique that combines limited calibration with the 1D algebraic scene-based algorithm. 17 The technique, however, was developed under the restrictive assumption of subpixel 1D motion. Here we present a major generalization of it that facilitates the integration of limited calibration with scene-based correction while utilizing image frames exhibiting global motion of arbitrary magnitude and direction [i.e., arbitrary 1D or twodimensional (2D) motion].…”

Section: Introductionmentioning

confidence: 99%

Radiometrically accurate scene-based nonuniformity correction for array sensors

2003

Self Cite

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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.

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Radiometrically calibrated scene-based nonuniformity correction for infrared array sensors

Cited by 12 publications

References 12 publications

An Algebraic Nonuniformity Correction Algorithm for Hexagonally-Sampled Infrared Images: A Simulation Study

An Algebraic Nonuniformity Correction Algorithm for Hexagonally-Sampled Infrared Images: A Simulation Study

Corrección de imágenes IR mediante un filtro extendido de estadísticas constantes

Radiometrically accurate scene-based nonuniformity correction for array sensors

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