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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (J. of the Korea Inst. of Information&Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (J. of the Korea Inst. of Information&Communication Engineering)

Current Result Document : 4 / 17 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) º¹ÇÕ ÀâÀ½ ȯ°æ¿¡¼­ °ø°£Àû Ư¼ºÀ» °í·ÁÇÑ ÀâÀ½ Á¦°Å
¿µ¹®Á¦¸ñ(English Title) Noise Removal with Spatial Characteristics in Mixed Noise Environment
ÀúÀÚ(Author) õºÀ¿ø   ±è³²È£   Bong-Won Cheon   Nam-Ho Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 23 NO. 03 PP. 0254 ~ 0260 (2019. 03)
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(Korean Abstract)
ÃÖ±Ù ´Ù¾çÇÑ ºÐ¾ß¿¡¼­ ¿µ»ó¸ÅüÀÇ »ç¿ë ºóµµ°¡ Áõ°¡ÇÔ¿¡ µû¶ó ½Åȣó¸®ÀÇ Á߿伺ÀÌ ³ô¾ÆÁö°í ÀÖ´Ù. ÇÏÁö¸¸ ¼Û¼ö½Å °úÁ¤¿¡¼­ ¸¹Àº Á¾·ùÀÇ ÀâÀ½ÀÌ ¹ß»ýÇÏ¸ç ½ÅÈ£ÀÇ Á¤º¸¿¡ ¿µÇâÀ» ¹ÌÄ¡°í ÀÖÀ¸¸ç, ÀÌ·¯ÇÑ ÀÌÀ¯·Î ÀâÀ½ Á¦°Å¸¦ Àüó¸® °úÁ¤À¸·Î¼­ ÇʼöÀûÀ¸·Î ÇàÇÑ´Ù. º» ³í¹®¿¡¼­´Â ÀÓÆÞ½º ÀâÀ½°ú AWGNÀÌ È¥ÇÕµÈ ÀâÀ½À» Á¦°ÅÇϱâ À§ÇÑ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÏ¿´´Ù. Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀº º¹ÇÕ ÀâÀ½ ȯ°æ¿¡¼­ È¿À²ÀûÀÎ ÀâÀ½ Á¦°Å¸¦ À§ÇØ ÀâÀ½ ÆÇ´ÜÀ» ÅëÇØ ¿µ»ó º¹¿øÀ» ÁøÇàÇϸç, °ø°£Àû Ư¼º°ú È­¼Ò º¯È­¸¦ °í·ÁÇÏ¿© ÀâÀ½À» Á¦°ÅÇÑ´Ù. ½Ã¹Ä·¹ÀÌ¼Ç °á°ú Á¦¾ÈÇÑ ¾Ë°í¸®ÁòÀº ±âÁ¸ ¹æ¹ý°ú ´Þ¸® µÎ ÀâÀ½ÀÇ ¿µÇâÀ» ¸ðµÎ ÃÖ¼ÒÈ­ÇÏ¿© ÀâÀ½À» Á¦°ÅÇÏ¿© ¿ì¼öÇÑ ÀâÀ½Á¦°Å Ư¼ºÀ» ³ªÅ¸³»¾úÀ¸¸ç, °´°üÀûÀÎ ÆÇ´ÜÀ» À§ÇØ PSNR ¹× ÇÁ·ÎÆÄÀÏ µîÀ» ÀÌ¿ëÇÏ¿© ºñ±³ ¹× ºÐ¼®ÇÏ¿´´Ù.
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(English Abstract)
Recently, the importance of signal processing has become gradually significant, as the frequency of video media increases in various fields. However, numerous kinds of noise generated in the transmission and reception processes can possibly affect the signal information, and the noise removal is for that reason essential as a preprocessing step. In this paper, we propose an algorithm to remove the mixed noise which is composed of impulse noise and AWGN. This algorithm is used for image restoration by noise judgment for efficient noise removal in a complex noise environment, and the noise is removed by considering spatial characteristics and pixel variations. Simulation results show that unlike existing methods, the algorithm has excellent noise cancellation characteristics by minimizing both noise effects and consequently eliminating the mixed noise; for objective judgment, we compared and analyzed the data using PSNR and profile.
Ű¿öµå(Keyword) º¹ÇÕÀâÀ½   ÀâÀ½ ÆÇ´Ü   ÇÊÅ͸µ   PSNR   Mixed noise   Noise judgment   Filtering   PSNR  
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