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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 :

ÇѱÛÁ¦¸ñ(Korean Title) º¹ÇÕ ÀâÀ½ ȯ°æ¿¡¼­ ¿µ»óÀÇ ÀâÀ½ ¼ººÐÀ» ÀÌ¿ëÇÑ ÇÊÅÍ ¾Ë°í¸®Áò
¿µ¹®Á¦¸ñ(English Title) A Filter Algorithm using Noise Component of Image in Mixed Noise Environments
ÀúÀÚ(Author) õºÀ¿ø   ±è³²È£   Bong-Won Cheon   Nam-Ho Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 23 NO. 08 PP. 0943 ~ 0949 (2019. 08)
Çѱ۳»¿ë
(Korean Abstract)
ÃÖ±Ù ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ µðÁöÅÐ ÀåºñÀÇ »ç¿ëÀÌ Áõ°¡ÇÔ¿¡ µû¶ó ¿µ»ó ¹× ½Åȣó¸®ÀÇ Á߿伺ÀÌ ³ô¾ÆÁö°í ÀÖ´Ù. ÇÏÁö¸¸ ½ÅÈ£ÀÇ ¼Û¼ö½Å °úÁ¤¿¡¼­ ´Ù¾çÇÑ ÀÌÀ¯·Î ÀâÀ½ÀÌ ¹ß»ýÇϸç, ÀÌ·¯ÇÑ ÀâÀ½Àº ½Ã½ºÅÛÀÇ ÃÖÁ¾ Ãâ·Â¿¡ Å« ¿µÇâÀ» ¹ÌÄ£´Ù. º» ³í¹®Àº S&P ÀâÀ½°ú AWGNÀÌ È¥ÇÕµÈ ÀâÀ½ ȯ°æ¿¡¼­ ¿µ»óÀÇ ÀâÀ½ Ư¼ºÀ» °í·ÁÇÏ¿© È¿°úÀûÀ¸·Î ¿µ»óÀ» º¹¿øÇÏ´Â ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÏ¿´´Ù. Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀº ¿µ»óÀÇ ÀâÀ½ ¼ººÐ À¯Ãß¿Í ÇÊÅ͸µ ¸¶½ºÅ© ³»ºÎÀÇ È­¼Ò Ư¼ºÀ» °í·ÁÇÏ¿© ¿µ»óÀÇ Æ¯Â¡À» º¸Á¸ÇÏ¿´À¸¸ç, ÀÔ·Â È­¼ÒÀÇ ¼ºÁú¿¡ µû¶ó ±âÁØÄ¡¸¦ ¼³Á¤ÇÏ¿© ÀÌ¿Í À¯»çÇÑ È­¼ÒµéÀ» ¼±º°ÇÏ¿© ÀâÀ½À» Á¦°ÅÇÏ¿´´Ù. ½Ã¹Ä·¹ÀÌ¼Ç °á°ú Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀº ¿ì¼öÇÑ ÀâÀ½Á¦°Å Ư¼ºÀ» ³ªÅ¸³»¾úÀ¸¸ç, ±âÁ¸ ¹æ¹ýµé°ú ºñ±³Çϱâ À§ÇØ PSNR µîÀ» ÀÌ¿ëÇÏ¿© ºñ±³ ¹× ºÐ¼®ÇÏ¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
As use of digital equipment in various fields is increasing importance of processing video and signals is rising as well. However, in the process of sending and receiving signals, noise occurs due to different reasons and this noise bring about a huge influence on final output of the system. This research suggests algorithm for effectively repairing video in consideration to characteristics of its noise in condition where impulse and AWGN noises are combined. This algorithm tries to preserve video features by considering inference to noise components and resolution of filtering mask. Depending on features of input resolution, standard value is set and similar resolutions is selected for noise removal. This algorithm showing simulation result had outstanding noise removal and is compared and analyzed with existing methods by using different ways such as PSNR.
Å°¿öµå(Keyword) ¿µ»ó󸮠  AWGN   S&P ÀâÀ½   PSNR   Image processing   AWGN   Salt and pepper noise   PSNR  
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