- Volume 11 Issue 5
DOI QR Code
Analysis I of Operator Adaptive Characteristic in the Noisy-Blurred Images: Gaussian blurred and additive 20dB noise
훼손된 영상에서의 연산자 적응 특성 분석 I : 가우시안으로 흐려지고 20dB 잡음이 추가된 훼손된 영상
- Received : 2010.02.05
- Accepted : 2010.05.13
- Published : 2010.05.31
The Laplacian operator is usually used as a regularization operator which may be used as any differential operator in the regularization iterative processing. In this paper, several kinds of differential operator and proposed operator as a regularization operator were compared with each other performance. For noisy gaussian-blurred images, proposed operator worked better in the edge, while in flat region the conventional operator resulted better. In regularization, smoothing the noise and restoring the edges should be considered at the same time, so the regions divided into the flat, the middle, and the detailed, which were processed in separate and compared.
- H. C. Andrews and B. R. Hunt, "Digital Image Restoration," Englewood Cliffs, NJ : Prentice-Hall, 1977.
- A. N. Tikhonov and V.Y. Arsenin, Solution of Ill-Posed Problem, Wiley, New York, 1977.
- S. Kawata and Y, Ichioka, "Iterative Image Restoration for linearly Degraded Image.Ⅰ.Basis," J. Opt. Soc. Amer., Vol.70, No.7, pp.762-768, July, 1980. https://doi.org/10.1364/JOSA.70.000762
- A. K. Katsaggelos, J. Biemond, R. W. Schafer and R. M. Mersereau, "A Regularized Iterative Image Restoration Algorithm," IEEE trans. signal processing, Vol.39, No.4, pp.914-929, April, 1991. https://doi.org/10.1109/78.80914
- R. L. Lagendijk , J. Biemond and D.E. Boekee, "Regularized Iterative Image restoration with Ringing Reduction," IEEE trans. ASSP, Vol.36, No.12, pp.1874-1888, December, 1988. https://doi.org/10.1109/29.9032
- Aggelos K. Katsaggelos, "Iterative Image Restoration Algorithms", Optical Eng., Vol. 28, No. 7, pp. 735-748, July 1989.
- Rafael C. Gonzalez, "Digital Image Processing", Addition Wesley, 1994.
- J. S. LIM, Two-Dimensional Signal and Image Processing, Prentice-Hall, 1990.