Image Modeling Appropriate for Kalman Filtering
碩士 === 國立中山大學 === 電機工程學系研究所 === 88 === In stochastic representation an image is a sample function of an array of random variables which is called a random field. For characterizing an ensemble of images, we choose an autoregressive model as our image model. An image model often applies to image pr...
Main Authors: | Kuo-Wei Tai, 戴國瑋 |
---|---|
Other Authors: | Ben-Shung Chow |
Format: | Others |
Language: | en_US |
Published: |
2000
|
Online Access: | http://ndltd.ncl.edu.tw/handle/39710983656880027662 |
Similar Items
-
Fuzzy Kalman Filter
by: Kuo-Hao Lee, et al.
Published: (2003) -
Design of Kalman Filters for State Estimation of Piezoelectric Vibration Gyroscopes
by: Tai-Wei Lin, et al.
Published: (2006) -
The Decentralized Extended Kalman Filtering for Multisensor Navigation
by: Kuo-Yang Tsao, et al.
Published: (1993) -
Comparison of the Extended Kalman Filter and the Unscented Kalman Filter for Magnetocardiography activation time imaging
by: H. Ahrens, et al.
Published: (2013-07-01) -
Data Fusion Based on Indirect Fuzzy Kalman Filter
by: Kuo-Long Tsao, et al.
Published: (2003)