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Spatial Compare Filter Based Real-Time dead Pixel Correction Method for Infrared Camera

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주제분류컴퓨터학

초록

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.

Abstract

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.

참고문헌 (11)

  1. W. Isoz, "Nonuniformity Correction of Infrared Focal Plane Arrays", Infrared Tech. Appli. Proc. SPIE, 5783, pp.949~960 (2005)
  2. Z. Jungju, "A nonuniformity correction algorithm for infrared focal-plane arrays", Proceedings of SPIE, 5640, pp.425~433 (2005)
  3. J. Harris, "Nonuniformity correction using the constant-statistics constraint : Analog and Digital Implementations", Proceedings of SPIE, 3061, pp.895~905 (1997)
  4. J. Harris, "Nonuniformity correction of infrared image sequences using the contant-statistics constraint", IEEE Trans. Image Processing, 8(8), pp.1148~1151 (1999)
  5. S. Tzimopoulou, "Scene based techniques for nonuniformity correction of infrared focal plane arrays", Proceedings of SPIE, 3436, pp.172~183 (1998)
  6. M. Voig, "Scene-Based Non-Uniformity Correction for Focal Plane Arrays using a Facet Model", Infrared Imaging Systems: Design, Analysis, Modelling and Testing XVI, Proc. SPIE, 5784, pp.331~342 (2002)
  7. 김철중, "Real-time small target detection method Using multiple filters and IPP Libraries in Infrared Images", 한국컴퓨터정보학회논문지, 21(8), pp.21~28 (2016), 한국컴퓨터정보학회
  8. 김재협, "적외선 영상에서 변위추정 및 SURF 특징을 이용한 표적 탐지 분류 기법", 한국컴퓨터정보학회논문지, 19(11), pp.43~52 (2014), 한국컴퓨터정보학회
  9. S. Qi, "A Robust Directional Saliency-Based Method for Infrared Small-Target Detection Under Various Complex Backgrounds", IEEE Trans. on Geoscience and Remote Sensing Letters, 10(3), pp.495~499 (2013)
  10. Y. Han, "Infrared small target detection based on spatio-temporal saliency in video sequence", IEEE 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp.279~282 (2015)
  11. 이임건, "방향성 정보와 적응적 언샾 마스크를 이용한 영상의 화질 개선", 한국컴퓨터정보학회논문지, 16(3), pp.27~34 (2011), 한국컴퓨터정보학회

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