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Video Restoration Based on Kalman Filtering

In this paper, we propose a Kalman filtering method to restore signal when both the digital and analog signal are available. The digital video signal is coded by method of MPEG. The error can be introduced in the quantization process of the block DCT transformation. So the quality of the image from the digital video signal needs to be improved. Considering the analog video signal is corrupted by the Gauss White Noise. We can apply the Kalman filter to these two signals at the same time to restore the image for a better quality.
The image structure is defined to be the linear relationship between pixels with their upper and left neighbors. So we can determinate the image structure property by the linear equations of the pixel gray level. Generally, the image segmentation takes the gray values as the property. In our case we take the linear equations as our property function. This property implies an abstract concept and can¡¦t measure directly. We determine the unity of the image structure by measuring the error from merging the pixel into one region. We achieve a recursive formula for computing the error by the sequential least square error method.
In the signal processing, Kalman filter is used for optimal estimation of the signal corrupted by additive noise. We segment the image by its local property. By our segmentation technique every region has its specific image structure. The structures are system parameters of Kalman filter.
We first utilize the method of segmentation on the image recovered from the MPEG signal to find the local parameters. The results of experiments show that we can improve the images quality when the MPEG signal is not very good.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0710101-124022
Date10 July 2001
CreatorsHung, Shau-Pin
ContributorsS.C.Tai, Ben-Shung Chow, Chin-Hsing Chen
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0710101-124022
Rightsnot_available, Copyright information available at source archive

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