DocumentCode :
2808526
Title :
Restoration method for degraded images using two-dimensional block Kalman filter with colored driving source
Author :
Nagayasu, Ryu ; Hosoda, Naoto ; Tanabe, Nari ; Matsue, Hideaki ; Furukawa, Toshihiro
Author_Institution :
Tokyo Univ. of Sci., Nagano, Japan
fYear :
2011
fDate :
4-7 Jan. 2011
Firstpage :
151
Lastpage :
156
Abstract :
This paper proposes a robust image restoration method using two-dimensional block Kalman filter with colored driving source. This method aims to achieve high quality image restoration for blur and noise disturbance from the canonical state space models with (i) a state equation composed of the original image, and (ii) an observation equation composed of the original image, blur, and noise. The remarkable feature of the proposed method is realization of high performance image restoration without sacrificing original image despite simple image restoration using only Kalman filter algorithm, while many conventional methods based on the Kalman filter theory usually perform the image restoration, using the parameter estimation algorithm of AR(auto regressive) system and the Kalman filter algorithm. We show the effectiveness of the proposed method using numerical results and subjective evaluation results.
Keywords :
Kalman filters; autoregressive processes; image colour analysis; image restoration; parameter estimation; 2d block Kalman filter; Kalman filter; autoregressive system; blur image; canonical state space models; colored driving source; image degradation; image restoration; noise; parameter estimation; AWGN; Equations; Estimation; Image restoration; Kalman filters; Mathematical model; PSNR; Image restoration; auto regressive; blur; colored driving source; noise; two-dimensional block Kalman filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop (DSP/SPE), 2011 IEEE
Conference_Location :
Sedona, AZ
Print_ISBN :
978-1-61284-226-4
Type :
conf
DOI :
10.1109/DSP-SPE.2011.5739203
Filename :
5739203
Link To Document :
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