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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Image Compression Using Wavelet Based Scalable Modeling of Residual Image

Lin, Wan-Shan 14 July 2000 (has links)
This thesis is based on the modified JPEG encoding which uses a preprocessing called as Cubic Convolution Spline Interpolation to subsample the original image into lower resolution image, the subsampled image is encoded by JPEG. The modified JPEG can get very high compression ratio, it¡¦s quality is better than the JPEG file which has the same compressing ratio, but it still is not good enough. In this thesis we use the scalable wavelet encoding to encode the residual image, which is the difference between original and compression image. Due to the high compressing ratio and scalablity. We can attach the compressed residual image with modified JPEG compressed image to get the scalable compressed image whose compressing ratio can tun from 125 to 50 and always get better quality than optimal JPEG.
2

Image Modeling Appropriate for Kalman Filtering

Tai, Kuo-Wei 28 July 2000 (has links)
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 processing such as image data compression and image restoration. Therefore the validity of the image model affect it¡¦s performance of image processing. The output of the AR model depends on its parameters ¡V system transition matrix and generating noise. Hence the validity of this model is related to these two parameters. How to seek the standard of the validity of the image model is a problem. We exploit performance of image model¡¦s application ¡V image restoration - to find a method of determining the validity of the image model. In our paper we find a relation between image restoration performance and image model¡¦s parameters by the Kalman filtering equations. An image model with lower generating noise power and system transition matrix is better for image restoration and is considered a good image model. In the analysis of the parameters of the image model, we can meet the requirements of the parameters by image segmentation method, residual image method and normalized image method. In addition it also helps us understand the Kalman filter much more and know how to find the solution of similar problems.

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