• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.67-74
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• 2018

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.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.213-218
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• 2013

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 373 K. Real-time imaging shows that the proposed method improves image quality better than traditional techniques.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.645-652
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• 2010

The performance of the payload Electro-Optical System (EOS) in satellite system is affected by various factors, such as optics design, camera electronics design, and the characteristics of the CCD (Charge Coupled Device) used, etc. Of these factors, the camera electronics design is somewhat unique in that its operational parameters can be adjusted even after the satellite launch. In this paper, the effect of video gain on the non-uniformity correction performance is addressed. And a new optimal non-uniformity correction scheme is proposed and analyzed using the data from real camera electronics unit based on a TDI (Time Delayed Integration) type of CCD. The test results show that the performance of the conventional non-uniformity correction scheme is affected significantly when the video gain is added. On the other hand, in our proposed scheme, the performance is not dependent on the video gain. The insensitivity of the non-uniformity performance on the video-gain is mainly due to the fact that the correction is performed after the dark signal is subtracted from system response.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.269-275
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• 2022

In ideal configuration, elapsed-time method can measure the exact reaction wheel speed. But in real configuration, the speed measurement error exists due to tacho pulse non-uniformity. In this research, we study the method which overcome the non-uniformity effects. First, we introduce the method which spin the wheel at the specific speed and measure the non-uniformity. Then, we propose the real-time measurement error correction method which uses the obtained non-uniformity information. This method calculate the speed candidates from the elapsed-time method's counts and non-uniformity information, and choose the closest speed to the real speed. Through simulation, we show that proposed method measure the exact speed regardless of non-uniformity, and fast wheel speed control is possible.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.35-41
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• 2016

In this paper, we propose a new real-time dead pixel detection method based on spatial compare filtering, which are usually used in the small target detection. Actually, the soft dead and the small target are cast in the same mold. Our proposed method detect and remove the dead pixels as applying the spatial compare filtering, into the pixel outputs of a detector after the non-uniformity correction. Therefore, we proposed method can effectively detect and replace the dead pixels regardless of the non-uniformity correction performance. In infrared camera, there are usually many dead detector pixels which produce abnormal output caused by manufactural process or operational environment. There are two kind of dead pixel. one is hard dead pixel which electronically generate abnormal outputs and other is soft dead pixel which changed and generated abnormal outputs by the planning process. Infrared camera have to perform non-uniformity correction because of structural and material properties of infrared detector. The hard dead pixels whose offset values obtained by non-uniformity correction are much larger or smaller than the average can be detected easily as dead pixels. However, some dead pixels(soft dead pixel) can remain, because of the difficulty of uncleared decision whether normal pixel or abnormal pixel.

• Current Optics and Photonics
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• v.7 no.4
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• pp.408-418
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• 2023

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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.29-33
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• 2007

All pixels of image sensor do not react uniformly even if the light of same radiance enters into the camera. This non-uniformity comes from the sensor pixel non-uniformity and non-uniformity induced by the changing transmission of the telescope over the field. The first contribution to the non-uniformity has high spatial frequency nature and has an influence on the result and quality of the data compression. The second source of non-uniformity has low frequency nature and has no influence of the compression result. As the contribution resulting from the sensor PRNU(Photo Response Non-Uniformity) is corrected inside the camera electronics, the effect of the remaining non-uniformity to the compression result will be negligible. The non-uniformity correction result shall have big difference according to the sensor modeling and the calculation method to get correction coefficient. Usually, the sensor can be modeled with one dimensional coefficients which are a gain and a offset for each pixel. Only two measurements are necessary theoretically to get coefficients. However, these are not the optimized value over the whole illumination level. This paper proposes the algorithm to calculate the optimized non-uniformity correction coefficients over whole illumination radiance. The proposed algorithm uses several measurements and the least square method to get the optimum coefficients. The proposed algorithm is verified using the own camera electronics including sensor, electrical test equipment and optical test equipment such as the integrating sphere.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.478-481
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• 2005

The PMU (Payload Management Unit) is the main subsystem for the management, control and power supply of the MSC (Multi-Spectral Camera) Payload operation. It is the most important function for the electro-optical camera system that performs the Non-Uniformity Correction (NUC) function of the raw imagery data, rearranges the data from the CCD (Charge Coupled Device) detector and output it to the Data Compression and Storage Unit (DCSU). The NUC board in PMU performs it. In this paper, the NUC board system is described in terms of the configuration and the function, the efficiency for non-uniformity correction, and the influence of the data compression upon the peculiar feature of the CCD pixel. The NUC board is an image-processing unit within the PMU that receives video data from the CEV (Camera Electronic Unit) boards via a hotlinkand performs non-uniformity corrections upon the pixels according to commands received from the SBC (Single Board Computer) in the PMU. The lossy compression in DCSU needs the NUC in on-orbit condition.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.207-213
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• 2017

In order to accurately perform multispectral imaging using a multiplexed illumination, intensity of illumination in a scene must be uniform. For image acquisition that requires accurate color information, even if not multispectral imaging, the illumination information must be accurate, and a flat light source or illumination calibration is performed for accurate illumination characteristics. In this paper, we propose a method of color correction to uniformly illuminate an image with non-uniform illumination intensity. The proposed method uses multispectral imaging instead of illumination calibration for color correction. First of all, we perform multispectral imaging with two images obtained from non-uniformity illumination to acquire spectral reflectance. The obtained reflection spectrum is relit as the illumination characteristic of the image obtained from general planar light such as fluorescent light or sunlight. By comparing the image obtained by relighting with the uniformly illuminated image, the non-uniformity of the illumination is confirmed, and the color correction is performed as the image obtained from the uniform image. It is expected that the experimental results will confirm whether the non-uniformity of the illumination is uniformly corrected and reduce the restriction of illumination in obtaining the color information of the image.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.305-307
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• 2007

KOMPSAT-2(K-2) 의 MSC 는 CCD pixel 별 band 별 특성, 감도 및 시간에 따른 변화, CCD Geometry 등에 의해 왜곡 현상이 일어나며 위성 발사 전에 실험실에서의 충분한 실험과 Calibration 작업 을 통해 얻어진 값들을 사용하여 Image Restoration, 상대 복사 보정, 절대 복사 보정 등의 작업들을 거쳐서 왜곡 현상을 보정하게 된다. 그 중 복사 보정에 해당하는 NUC(NonUniformity Correction)은 MSC 각각의 픽셀들이 상이한 특성을 나타내는 것을 균일한 이미지로 보정하는 작업으로 무엇보다 우선시 되는 검보정 작업이다. K-2 NUC table 생성에는 시스템 특성상 몇 가지 사항을 고려 하여 위성에 upload 하는 high frequency NUC(HF NUC)과 지상국에서 처리할 수 있는 low frequency NUC(LF NUC)으로 구분하여 알고리즘을 생성하였다.