A Improved Scene based Non-uniformity Correction Algorithm for Infrared Camera

Ho-Jin Hyun(현호진),Byung-In Choi(최병인) 한국컴퓨터정보학회 2018 韓國컴퓨터情報學會論文誌 Vol.23 No.1

In this paper, we propose an efficient scene based non-uniformity correction algorithm which performs the offset correction using the uniform obtained from input scenes for Infrared camera. In general, pixel outputs of a infrared detector can not be uniform. Therefore, the non-uniformity correction procedure need to be performed to make the image outputs uniform. A typical non-uniformity correction method uses a black body at the laboratory to obtain the output of the infrared detector’s pixels for two temperatures, HOT and COLD, and calculates the non-uniformity correction parameters. However, output characteristics of the Infrared detector changes while the Infrared camera is operated, the fixed pattern noise of the Infrared detector and dead pixels are generated. To remove the noise, the offset correction is generally performed. The offset correction procedure usually need the additional device such as a thermo-electric cooler, shutter, or non-uniformity correction lens. Therefore, we introduce a general scene based non-uniformity correction technique without additional equipment, and then we propose an improved non-uniformity correction algorithm based on image to solve the problem of the existing technique.

Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

Masami Goto,Osamu Abe,Tosiaki Miyati,Hiroyuki Kabasawa,Hidemasa Takao,Naoto Hayashi,Tomomi Kurosu,Takeshi Iwatsubo,Fumio Yamashita,Hiroshi Matsuda,Harushi Mori,Akira Kunimatsu,Shigeki Aoki,Kenji Ino,K 대한영상의학회 2012 Korean Journal of Radiology Vol.13 No.4

Objective: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 x [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. Objective: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 x [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.

New Non-uniformity Correction Approach for Infrared Focal Plane Arrays Imaging

Qu Hui-Ming,Gong Jing-tan,Huang Yuan,Chen Qian 한국광학회 2013 Current Optics and Photonics Vol.17 No.2

Although infrared focal plane array (IRFPA) detectors have been commonly used, non-uniformity correction (NUC) remains an important problem in the infrared imaging realm. Non-uniformity severely degrades image quality and affects radiometric accuracy in infrared imaging applications. Residual non-uniformity (RNU) significantly affects the detection range of infrared surveillance and reconnaissance systems. More effort should be exerted to improve IRFPA uniformity. A novel NUC method that considers the surrounding temperature variation compensation is proposed based on the binary nonlinear non-uniformity theory model. The implementing procedure is described in detail. This approach simultaneously corrects response nonlinearity and compensates for the influence of surrounding temperature shift. Both qualitative evaluation and quantitative test comparison are performed among several correction technologies. The experimental result shows that the residual non-uniformity, which is corrected by the proposed method,is steady at approximately 0.02 percentage points within the target temperature range of 283 K to 373K. Real-time imaging shows that the proposed method improves image quality better than traditional techniques.

An Efficient Technique for Non-Uniformity Correction of Infrared Video Sequences with Histogram Matching

Abbass Mohammed Y.,Sadic Nevein,Ashiba Huda I.,Hassan Emad S.,El-Dolil Sami,Soliman Naglaa F.,Algarni Abeer D.,Alabdulkreem Eatedal A.,Algarni Fatimah,El-Banby Ghada M.,Abdel-Rahman Mohamed R.,Aldosar 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.5

Infrared (IR) image sequences are acquired with certain types of cameras. These cameras give the sequence of images according to the heat distribution. With time, some deterioration of the quality of the sequence occurs due the thermal noise eff ect generated in the camera. This thermal noise eff ect leads to some sort of non-uniformity in the obtained image sequence. Hence, it is necessary to perform some sort of non-uniformity correction in the video sequence according to the fi rst frame. This type of non-uniformity correction is scene-based. This paper introduces a scene-based non-uniformity correction technique that depends mainly on histogram matching. The noise eff ect on each frame in the sequence leads to some drift in the histogram of that frame. Hence, the proposed technique depends on the histogram matching concept to correct the histogram of each frame in the sequence based on the histogram of the fi rst frame that is free from the thermal noise eff ect. Diff erent image quality metrics including entropy, contrast, edge intensity, average gradient, and correlation with the fi rst frame are adopted to assess the quality of the obtained frames after adjustment. It is required in the frames to be corrected to reduce entropy, edge intensity and average gradient as these metrics are increased with the presence of thermal noise eff ect on all pixels represented as much details and unnecessary information. In addition, the contrast of the video sequences should be increased to determine objects in a better way. The correlation of the corrected frames with the fi rst one should be increased to reduce the noise eff ect. Simulation results reveal enhanced quality of the obtained video sequences after processing with the proposed technique.

A Non-uniform Correction Algorithm Based on Scene Nonlinear Filtering Residual Estimation

Hongfei Song,Kehang Zhang,Wen Tan,Fei Guo,Xinren Zhang,Wenxiao Cao 한국광학회 2023 Current Optics and Photonics Vol.7 No.4

Due to the technological limitations of infrared thermography, infrared focal plane array (IFPA) imaging exhibits stripe non-uniformity, which is typically fixed pattern noise that changes over time and temperature on top of existing non-uniformities. This paper proposes a stripe non-uniformity correction algorithm based on scene-adaptive nonlinear filtering. The algorithm first uses a nonlinear filter to remove single-column non-uniformities and calculates the actual residual with respect to the original image. Then, the current residual is obtained by using the predicted residual from the previous frame and the actual residual. Finally, we adaptively calculate the gain and bias coefficients according to global motion parameters to reduce artifacts. Experimental results show that the proposed algorithm protects image edges to a certain extent, converges fast, has high quality, and effectively removes column stripes and non-uniform random noise compared to other adaptive correction algorithms.

사이드 슬리더 촬영 기반 KOMPSAT-3 위성 영상의 균일 영역 검출을 통한 비균일 보정 기법 연구 양식

김현호 ( Hyun-ho Kim ),서두천 ( Doochun Seo ),정재헌 ( Jaeheon Jung ),김용우 ( Yongwoo Kim ) 대한원격탐사학회 2021 大韓遠隔探査學會誌 Vol.37 No.5

KOMPSAT-3로 촬영한 영상은 일반 카메라로 촬영한 영상과 달리 가시광선 대역의 RGB 영역뿐만 아니라 NIR, PAN Band를 추가적으로 가지고 있다. 또한, 지상 685 km의 높은 고도에서 약 17 km 이상이 되는 넓은 반경의 지역을 촬영하기 때문에 이에 따른 전기적, 광학적 특성을 고려해야 한다. 즉, KOMPSAT-3의 카메라 센서는 각 CCD 픽셀 별, 각 band 별 특성, 감도 및 시간에 따른 변화, CCD Geometry 등에 의해 왜곡 현상이 발생하는데, 왜곡 현상을 해결하기 위해 센서보정이 필수적으로 필요하다. 본 논문에서는 KOMPSAT-3 사이드 슬리더 촬영 기반 영상에서 세그먼트 기반 노이즈 분석을 통한 균일 영역을 검출하는 기법을 제안한다. 해당 알고리즘을 통해 균일 영역을 검출 후 비 균일 보정 알고리즘 적용을 위해 각 센서별로 보정 테이블을 생성한 후 생성된 보정 테이블을 이용하여 위성 영상 보정을 수행하였다. 그 결과 기존 기법 대비 제안한 기법을 통해 수직 노이즈와 같은 위성 영상의 왜곡을 감소하였으며, 영상 품질의 척도인 상대적 방사 정확성 지표에 대해서는 평균 제곱 오차를 사용한 지표(RA)와 절대오차를 이용한 지표(RE)에 대해서 기존 방법에 대비하여 각각 0.3%, 0.15% 평가 지표에서 비교 우위에 있음을 확인하였다. Images taken with KOMPSAT-3 have additional NIR and PAN bands, as well as RGB regions of the visible ray band, compared to images taken with a standard camera. Furthermore, electrical and optical properties must be considered because a wide radius area of approximately 17 km or more is photographed at an altitude of 685 km above the ground. In other words, the camera sensor of KOMPSAT-3 is distorted by each CCD pixel, characteristics of each band, sensitivity and time-dependent change, CCD geometry. In order to solve the distortion, correction of the sensors is essential. In this paper, we propose a method for detecting uniform regions in side-slider-based KOMPSAT-3 images using segment-based noise analysis. After detecting a uniform area with the corresponding algorithm, a correction table was created for each sensor to apply the non-uniformity correction algorithm, and satellite image correction was performed using the created correction table. As a result, the proposed method reduced the distortion of the satellite image, such as vertical noise, compared to the conventional method. The relative radiation accuracy index, which is an index based on mean square error (RA) and an index based on absolute error (RE), was found to have a comparative advantage of 0.3 percent and 0.15 percent, respectively, over the conventional method.

픽셀 비선형성 모델을 기반으로 한 영상센서 불균일 특성 보정

김영선(Youngsun Kim),공종필(Jong-Pil Kong),허행팔(Haeng-Pal Heo),박종억(Jong-Euk Park),용상순(Sang-Soon Yong) 한국항공우주연구원 2010 항공우주기술 Vol.9 No.1

균일한 광량의 빛이 카메라에 입력되었을 때 카메라 영상센서 각 픽셀은 이상적으로는 균일한 응답을 보여주어야 하지만 실제로는 그렇지 않다. 이러한 픽셀의 불균일 응답 특성은 영상품질에 직접적으로 영향을 미치지만, 고정된 형태의 잡음이므로 보정과정을 통해서 잡음을 제거할 수 있다. 영상센서 불균일 보정 방법은 특정 광량에서의 기준값만을 가지고 보정계수를 구하는 방법 등을 사용하곤 했지만, 센서의 비선형성으로 인하여 신호가 작은 경우, 혹은 반대로 아주 큰 경우에서는 보정 효과가 크지 않다. 따라서, 본 논문에서는 이러한 영상센서의 비선형 특성을 고려하여 픽셀 불균일 보정계수 계산하는 방법을 기술하고 자체 구현한 카메라와 별도의 시험셋업을 이용하여 불균일도 시험을 수행하여 알고리즘을 검증하였다. 시험결과는 비선형성 모델을 기반으로 한 보정 알고리즘을 적용했을 때, 모든 광량에서 가장 좋은 성능을 보여주었다. All pixels of image sensor do not react uniformly when the light of same radiance enters into the camera. This non-uniformity has a direct influence on the image quality. However we can overcome it by calibration process under the special test-setup. Usually it is used the algorithm to get the correction coefficients under the specific illumination condition. But, this method has drawback in the very low or very high illumination due to pixel non-linearity. This paper describes the robust algorithm, which calculates the correction coefficients based on the pixel non-linearity model, against the whole radiance. The paper shows the non-uniformity test results with the own camera and the specified test equipments as well. The results shows the best performance over the entire radiance when this method is applied.

적외선 비디오에서 Gain과 Offset 결합 보정을 통한 고정패턴잡음 제거기법

김성민(Seong Min Kim),배윤성(Yoonsung Bae),장재호(Jae Ho Jang),나종범(Jong Beom Ra) 大韓電子工學會 2012 電子工學會論文誌-SP (Signal processing) Vol.49 No.2

대부분의 최근 적외선 센서는 focal-plane array (FPA) 구조로 되어있다. 이러한 구조의 센서는 공간적 불균일 응답성을 갖는 것으로 알려져 있고, 이로 인해 고정패턴잡음을 발생시킴으로써 영상열화를 가져온다. 따라서 적외선 영상의 고정패턴잡음을 제거하기 위해서는 픽셀 불균일 보정을 해야 한다. 픽셀 불균일 보정기법은 참조물체기반 접근법과 영상기반 접근법으로 나눌 수 있다. 참조물체기반 접근법에서는 흑체와 같은 균일한 온도를 갖는 물체를 이용해서 고정패턴잡음을 분리시킬 수 있는 방법이다. 하지만 센서의 응답성은 시간이 지나면서 변할 수 있기 때문에, 최근에는 비디오 영상을 이용하는 영상기반 접근법이 많이 연구되고 있다. 영상기반 접근법들 중에서 칼만 필터를 기반으로 하는 최신 알고리듬은 영상 간에 움직임 보상 시에 한 방향 워핑을 이용하고 센서의 offset 불균일성만을 보상해준다. 하지만 한 방향 워핑을 이용한 시스템 모델은 영상의 경계 부근에서 고정패턴잡음을 효과적으로 제거하지 못한다. 게다가, offset만 보정하는 접근법은 gain의 불균일성의 영향을 많이 받는 영상에서는 성능이 악화될 수 있다. 그러므로 본 논문에서는 양방향 워핑을 이용하여 시스템 모델링을 하고, gain과 offset의 결합 보정을 수행하는 알고리듬을 제안한다. 모사 영상과 실제 영상에 대한 실험 결과들은 제안하는 알고리듬이 기존 알고리듬들보다 더 효과적으로 고정패턴잡음을 제거하는 것을 확인할 수 있다. Most recent infrared (IR) sensors have a focal-plane array (FPA) structure. Spatial non-uniformity of a FPA structure, however, introduces unwanted fixed pattern noise (FPN) to images. This non-uniformity correction (NUC) of a FPA can be categorized into target-based and scene-based approaches. In a target-based approach, FPN can be separated by using a uniform target such as a black body. Since the detector response randomly drifts along the time axis, however, several scene-based algorithms on the basis of a video sequence have been proposed. Among those algorithms, the state-of-the-art one based on Kalman filter uses one-directional warping for motion compensation and only compensates for offset non-uniformity of IR camera detectors. The system model using one-directional warping cannot correct the boundary region where a new scene is being introduced in the next video frame. Furthermore, offset-only correction approaches may not completely remove the FPN in images if it is considerably affected by gain non-uniformity. Therefore, for FPN reduction in IR videos, we propose a joint correction algorithm of gain and offset based on bi-directional warping. Experiment results using simulated and real IR videos show that the proposed scheme can provide better performance compared with the state-of-the art in FPN reduction.

A Wide Dynamic Range NUC Algorithm for IRCS Systems

Li-Hua Cai,Feng-Yun He,Song-Tao Chang,Zhou Li 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.73 No.12

Uniformity is a key feature of state-of-the-art infrared focal planed array (IRFPA) and infrared imaging system. Unlike traditional infrared telescope facility, a ground-based infrared radiant char- acteristics measurement system with an IRFPA not only provides a series of high signal-to-noise ratio (SNR) infrared image but also ensures the validity of radiant measurement data. Normally, a long integration time tends to produce a high SNR infrared image for infrared radiant charac- teristics radiometry system. In view of the variability of and uncertainty in the measured target's energy, the operation of switching the integration time and attenuators usually guarantees the gual- ity of the infrared radiation measurement data obtainted during the infrared radiant characteristics radiometry process. Non-uniformity correction (NUC) coecients in a given integration time are often applied to a specified integration time. If the integration time is switched, the SNR for the infrared imaging will degenerate rapidly. Considering the effect of the SNR for the infrared image and the infrared radiant characteristics radiometry above, we propose a-wide-dynamic-range NUC algorithm. In addition, this essasy derives and establishes the mathematical modal of the algorithm in detail. Then, we conduct verification experiments by using a ground-based MWIR(Mid-wave Infared) radiant characteristics radiometry system with an 400 mm aperture. The experimental results obtained using the proposed algorithm and the traditional algorithm for different integration time are compared. The statistical data shows that the average non-uniformity for the proposed algorithm decreased from 0.77% to 0.21% at 2.5 ms and from 1.33% to 0.26% at 5.5 ms. The testing results demonstrate that the usage of suggested algorithm can improve infrared imaging quality and radiation measurement accuracy.

PIXEL-BASED CORRECTION METHOD FOR GAFCHROMIC^®EBT FILM DOSIMETRY

Jeong, Hae-Sun,Han, Young-Yih,Kum, O-Yeon,Kim, Chan-Hyeong,Ju, Sang-Gyu,Shin, Jung-Suk,Kim, Jin-Sung,Park, Joo-Hwan Korean Nuclear Society 2010 Nuclear Engineering and Technology Vol.42 No.6

In this paper, a new approach using a pixel-based correction method was developed to fix the non-uniform responses of flat-bed type scanners used for radiochromic film dosimetry. In order to validate the method's performance, two cases were tested: the first consisted of simple dose distributions delivered by a single port; the second was a complicated dose distribution composed of multiple beams. In the case of the simple individual dose condition, ten different doses, from 8.3 cGy to 307.1 cGy, were measured, horizontal profiles were analyzed using the pixel-based correcton method and compared with results measured by an ionization chamber and results corrected using the existing correction method. A complicated inverse pyramid dose distribution was made by piling up four different field shapes, which were measured with GAFCHROMIC$^{(R)}$EBT film and compared with the Monte Carlo calculation; as well as the dose distribution corrected using a conventional method. The results showed that a pixel-based correction method reduced dose difference from the reference measurement down to 1% in the flat dose distribution region or 2 mm in a steep dose gradient region compared to the reference data, which were ionization chamber measurement data for simple cases and the MC computed data for the complicated case, with an exception for very low doses of less than about 10 cGy in the simple case. Therefore, the pixel-based scanner correction method is expected to enhance the accuracy of GAFCHROMIC$^{(R)}$EBT film dosimetry, which is a widely used tool for two-dimensional dosimetry.