Image restoration using fast modified reduced update Kalman filter

Wen-Rong Wu*, Amlan Kundu

*Corresponding author for this work

研究成果: Paper同行評審

摘要

Some modifications to the reduced update Kalman filter (RUKF) as applied to the filtering of images corrupted by additive noise are proposed. The computational complexity of RUKF is reduced by reducing the state dimensionality. The RUKF is modified using the score-function-based approach to accommodate the non-Gaussian noise. The image is modeled as a nonstationary mean and stationary variance autoregressive Gaussian process. It is shown that the stationary variance assumption is reasonable if the nonstationary mean is computed by means of an edge and detail preserving spatial filter. Such a filter is described.

原文English
頁面547-550
頁數4
DOIs
出版狀態Published - 9 八月 1990
事件Proceedings of the 1990 IEEE International Conference on Systems Engineering - Pittsburgh, PA, USA
持續時間: 9 八月 199011 八月 1990

Conference

ConferenceProceedings of the 1990 IEEE International Conference on Systems Engineering
城市Pittsburgh, PA, USA
期間9/08/9011/08/90

指紋 深入研究「Image restoration using fast modified reduced update Kalman filter」主題。共同形成了獨特的指紋。

引用此