Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)
Current Result Document : 3 / 3
ÇѱÛÁ¦¸ñ(Korean Title) |
¹è°æ ÀâÀ½ Á¦°Å ¾Ë°í¸®ÁòÀ» Àû¿ëÇÑ 3Â÷¿ø ±¤ÀÚ °è¼ö ÁýÀû ¿µ»óÀÇ ÈÁú Çâ»ó |
¿µ¹®Á¦¸ñ(English Title) |
Visual quality enhancement of three-dimensional photon-counting integral imaging using background noise removal algorithm |
ÀúÀÚ(Author) |
Á¶±â¿Á
±è¿µÁØ
±èö¼ö
Á¶¸íÁø
Ki-Ok Cho
Young jun Kim
Cheolsu Kim
Myungjin Ch
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¿ø¹®¼ö·Ïó(Citation) |
VOL 20 NO. 07 PP. 1376 ~ 1382 (2016. 07) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®¿¡¼´Â, ¹è°æ ÀâÀ½ Á¦°Å ¾Ë°í¸®ÁòÀ» Àû¿ëÇÏ¿© ÀϹÝÀûÀÎ 3Â÷¿ø ±¤ÀÚ °è¼ö ÁýÀû ¿µ»óÀÇ ÈÁúÀ» °³¼±ÇÏ´Â ¹æ¹ýÀ» ¼³¸íÇÑ´Ù. ±¤ÀÚ °è¼ö ¿µ»ó¹ýÀº ±¤ÀÚ°¡ ¸Å¿ì Èñ¹ÚÇÑ È¯°æ¿¡¼ ¼Ò¼öÀÇ ±¤ÀÚ¸¦ °ËÃâÇÏ¿© ¿µ»óÀ» ½Ã°¢È ÇÏ´Â ¹æ¹ýÀÌ´Ù. ÇÏÁö¸¸, ¹è°æ¿¡¼ ¹ß»ýµÇ´Â ±¤ÀÚÀÇ ¼ö°¡ ¸¹À» ¶§, ¿øÇÏ´Â ¹°Ã¼ÀÇ ±¤ÀÚ °ËÃâÀº ¸Å¿ì ¾î·Æ´Ù. ÀÌ·Î ÀÎÇØ, º¹¿øµÈ ¿µ»óÀÇ ÈÁúÀÌ ÀúÇϵǴ ¹®Á¦Á¡ÀÌ ÀÖ´Ù. µû¶ó¼, º» ³í¹®¿¡¼´Â ºÒÇÊ¿äÇÑ ¹è°æ ÀâÀ½À» Á¦°ÅÇÏ°í ¿À·ÎÁö ¿øÇÏ´Â ¹°Ã¼¿¡¼¸¸ ±¤ÀÚ¸¦ °ËÃâÇÏ´Â »õ·Î¿î ±¤ÀÚ °è¼ö ¿µ»ó¹ýÀ» Á¦¾ÈÇÑ´Ù. ¶ÇÇÑ, 3Â÷¿ø Á¤º¸¸¦ ȹµæÇϱâ À§ÇØ ÁýÀû ¿µ»óÀ» »ç¿ëÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀÇ À¯¿ë¼ºÀ» Áõ¸íÇϱâ À§ÇÏ¿© ±¤ÇÐÀû ½ÇÇèÀ» ¼öÇàÇÏ°í ¼º´É Æò°¡¸¦ À§ÇØ Æò±Õ Á¦°ö ¿À·ù °ªÀ» °è»êÇÑ´Ù.
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¿µ¹®³»¿ë (English Abstract) |
In this paper, we present a visual quality enhancement technique for conventional three-dimensional (3D) photon counting integral imaging using background noise removal algorithm. Photon counting imaging can detect a few photons from desired objects and visualize them under severely photon-starved conditions such as low light level environment. However, when a lot of photons are generated from background, it is difficult to detect photons from desired objects. Thus, the visual quality of the reconstructed image may be degraded. Therefore, in this paper, we propose a new photon counting imaging method that removes unnecessary background noise and detects photons from only desired objects. In addition, integral imaging can be used to obtain 3D information and visualize the 3D image by statistical estimations such as maximum likelihood estimation. To prove and evaluate our proposed method, we implement the optical experiment and calculate mean square error.
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Å°¿öµå(Keyword) |
3D µð½ºÇ÷¹ÀÌ
±íÀÌ º¯È¯
¿ä¼Ò ¿µ»ó
ÁýÀû ¿µ»ó
Á¤Ä¡ ¿µ»ó µð½ºÇ÷¹ÀÌ
3D display
depth conversion
elemental images
integral imaging
orthosocpic display
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