AWGN 환경에서 화소 분포를 고려한 영상복원 알고리즘 = Image Restoration Algorithm Considering Pixel Distribution in AWGN Environments

다국어 초록 (Multilingual Abstract)

Recently, demand for digital image processing devices increases rapidly, more clear images have been required. But, in the process of digital image acquisition, processing and transmission, image degradation occurs due to various external reasons and researches about noise reduction are on the rise. Therefore, this study suggested the algorithm to process AWGN(additive white Gaussian noise) by separately processing as three levels according to the pixel distribution in the mask in order to remove AWGN(additive white Gaussian noise) which is added in the image. Regarding the processed results by applying Barbara images which were damaged by AWGN(σ = 15), suggested algorithm showed the improvement by 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB] and 1.25[dB] respectively compared with the existing MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF(3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5).

참고문헌 (Reference)

1 Xu Long, "복합잡음 환경에서 비선형 필터를 사용한 영상복원" 한국정보통신학회 17 (17): 2447-2453, 2013

2 권세익, "복합잡음 환경에서 변형된 공간 가중치 필터에 관한 연구" 한국정보통신학회 19 (19): 237-243, 2015

3 Jiahui Wang, "a New Selt-Adaptive Weighted Filter for Removing Noise in Infrared images" 2009

4 R. C. Gonzalez, "Digital Image Processing" Prentice Hall 2007

5 K. N. Plataniotis, "Color Image Processing and Applications" Springer 2000

6 You Ying-rong, "Adaptive filtering based on neighborhood information" 25 (25): 82-85, 2005

7 Öten, Remzi, "Adaptive Alpha-Trimmed Mean Filters Under Deviations From Assumed Noise Model" 13 (13): 627-639, 2004

8 Gao Yinyu, "AWGN환경에서 에지보호를 위한 개선된 잡음제거 알고리즘에 관한 연구" 한국정보통신학회 16 (16): 1773-1778, 2012

9 Xu Long, "AWGN 환경에서 영상복원 필터에 관한 연구" 한국정보통신학회 18 (18): 949-956, 2014

10 Xu Long, "AWGN 제거를 위한 개선된 가중치 필터" 한국정보통신학회 17 (17): 1227-1232, 2013