GELOMBANG-SINGKAT UNTUK PEMAMPATAN CITRA SEKUENSIAL

• Main Authors: , ALBERTUS JOKO SANTOSO, , Ir. Lukito Edi Nugroho, M.Sc., Ph.D.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2012
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/99012/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54927
• Institution: Universitas Gadjah Mada

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.