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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document : 11 / 13 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) GPGPU ±â¹ÝÀÇ ±íÀÌ ¿µ»ó È­Áú °³¼± ±â¹ý
¿µ¹®Á¦¸ñ(English Title) GPGPU based Depth Image Enhancement Algorithm
ÀúÀÚ(Author) ÇÑÀ翵   °íÁø¿õ   À¯Áö»ó   Jae-Young Han   Jin-Woong Ko   Jisang Yoo  
¿ø¹®¼ö·Ïó(Citation) VOL 17 NO. 12 PP. 2927 ~ 2936 (2013. 12)
Çѱ۳»¿ë
(Korean Abstract)
º» ³í¹®¿¡¼­´Â 3D ÄÜÅÙÃ÷ »ý¼º ½Ã ÇÊ¿äÇÑ ±íÀÌ ¿µ»óÀÇ È­Áú °³¼±À» À§ÇÏ¿© ÀâÀ½ Á¦°Å ±â¹ý°ú Ȧ ä¿ò ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ±â¹ý¿¡¼­´Â Ä÷¯ ¿µ»ó°ú ±íÀÌ ¿µ»óÀ» ¸ðµÎ ÀÌ¿ëÇÏ°Ô µÈ´Ù. ¸ÕÀú ÀÔ·ÂµÈ Ä÷¯ ¿µ»óÀ» RGB »ö»ó°è¿¡¼­ HSI »ö»ó°è·Î º¯È¯ÇÏ¿© ¹à±â ¿µ»óÀ» »ý¼ºÇÑ´Ù. ±×¸®°í ±íÀÌ ¿µ»ó¿¡¼­ ±âÁØ È­¼Ò¿Í ÁÖº¯ È­¼Ò°£ÀÇ °Å¸® °ª, ±íÀÌ °ªÀÇ Â÷À̸¦ ±¸ÇÏ°í Ä÷¯ ¿µ»óÀÇ ¹à±â °ª Â÷À̸¦ °è»êÇÏ¿© Á¦¾ÈÇÏ´Â ÀâÀ½ Á¦°Å ±â¹ý¿¡ ÀÌ¿ëÇÑ´Ù. ÀÌÈÄ È¦À» Ž»öÇÏ¿© Ȧ°ú ÁÖº¯ È­¼Ò°£ÀÇ °Å¸®, Ä÷¯ ¿µ»óÀÇ ¹à±â °ª Â÷À̸¦ Á¦¾ÈÇϴ Ȧ ä¿ò ±â¹ýÀ» Àû¿ëÇÏ¿© ±íÀÌ ¿µ»ó ³»¿¡ Á¸ÀçÇϴ ȦÀ» ä¿ì°Ô µÈ´Ù. ¸¶Áö¸·À¸·Î ½Ç½Ã°£ ȯ°æ¿¡ Àû¿ëÇϱâ À§ÇÏ¿© Á¦¾ÈÇÏ´Â ±â¹ýÀ» GPU·Î º´·ÄÈ­ÇÏ¿© ¼Óµµ Çâ»óÀ» ÇÏ°íÀÚ ÇÏ¿´´Ù. ½ÇÇèÀ» ÅëÇÏ¿© Á¦¾ÈÇÑ ±â¹ýÀÌ ±âÁ¸ ±â¹ý¿¡¼­ ¹ß»ýÇÏ´Â °æ°è ºÎºÐÀÇ Èå·ÁÁü Çö»óÀ» ÁÙÀ̸鼭 ȦÀ» ä¿ì´Â °ÍÀ» È®ÀÎÇÏ¿´´Ù.
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(English Abstract)
In this paper, we propose a noise reduction and hole removal algorithm in order to improve the quality of depth images when they are used for creating 3D contents. In the proposed algorithm, the depth image and the corresponding color image are both used. First, an intensity image is generated by converting the RGB color space into the HSI color space. By estimating the difference of distance and depth between reference and neighbor pixels from the depth image and difference of intensity values from the color image, they are used to remove noise in the proposed algorithm. Then, the proposed hole filling method fills the detected holes with the difference of euclidean distance and intensity values between reference and neighbor pixels from the color image. Finally, we apply a parallel structure of GPGPU to the proposed algorithm to speed-up its processing time for real-time applications. The experimental results show that the proposed algorithm performs better than other conventional algorithms. Especially, the proposed algorithm is more effective in reducing edge blurring effect and removing noise and holes.
Å°¿öµå(Keyword) ±íÀÌÁöµµ   ±íÀÌÁöµµ Ç°Áú Çâ»ó   ÀâÀ½ Á¦°Å   Ȧ ä¿ò   depth map   depth map enhancement   noise removal   hole filling  
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