| Summary: | The research for this dissertation has two objectives: to compare some wavelets
towards PSNR and compression ratio percentage and to find new wavelet filter
coefficient based on sequential images that can provide alternatives in coping with image
data compression problems by using the PSNR and ratio compression percentage. The
addition of new wavelets filter coefficient hopefully can hive more benefits compared to
the old existing wavelets.
The research is divided into three stages. The first is comparing 17 wavelets in
compressing still images. The second is comparing 17 wavelets in compressing
sequential images. While the last is finding the filter coefficient of new wavelets towards
sequential images. The correlation of the three stages is that the results of the first and
second stages, which is in the forms of the best values of PSNR and compression in each
of the families, is then used in comparison with the new wavelet filter coefficient.
Based on the result of the wavelet testing in still image compression and
sequential images, it is found that Haar, Coiflet 3 and Symlet 5 produce the highest
PSNR in each of their families. While the ones resulting in the highest compression ratio
percentage are Haar, Coiflet 1 and Symlet 2. The results if the third stage research show
that the steps stated can be applied in searching and finding new wavelet filter coefficient
based on sequential images. Besides, the results produce the best PSNR value and the
same compression ratio percentage when compared to Symlet 2 and even better when
compared to Coiflet 1.
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