@article{oai:miyazaki-u.repo.nii.ac.jp:00002635,
 author = {山森, 一人 and Yamamori, Kunihito and 山田, 義治 and 相川, 勝 and Aikawa, Masaru and Yamada, Yoshiharu},
 journal = {宮崎大学工学部紀要, Memoirs of Faculty of Engineering, University of Miyazaki},
 month = {Aug},
 note = {This paper proposes an image restoration method from degraded images which include additive gaussian noise and impulse noise. This method tries to achieve image restoration by using combination of canonical state space model kalman filter and median filter. Kalman filter estimates internal state of a dynamic system based on system model. The canonical state space models are described by two equations; state equation that expresses a transition process of the region including the focusing pixel of the image, and observation equation that expresses a process to add a noise to the original image. Image restoration by canonical state space model kalman filter can avoid to estimate system parameter, so restoration is faster than that by previous AR model kalman filter. Median filter rewrites a focusing pixel value by the median of the neighboring region of the focusing pixel. By comparing the differences between estimated pixel value of the kalman filter and median value of the median filter, our method decides which pixel value should be accepted whether estimated value by kalman filter or the median. Proposed method shows that signal to noise ratio is improved up to 10.70(dB).},
 pages = {233--237},
 title = {カルマン・メディアン複合フィルタによるガウス・インパルス混合雑音抑制法},
 volume = {42},
 year = {2013},
 yomi = {ヤマモリ, クニヒト and ヤマダ, ヨシハル and アイカワ, マサル}
}