Kompresi Spasio-Temporal Video Digital Menggunakan Geometric Wavelet

Rifka, Silfia (2008) Kompresi Spasio-Temporal Video Digital Menggunakan Geometric Wavelet. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Video saat ini digunakan dalam berbagai aplikasi yang berbeda, seperti video conference, diagnosis ilmu kedokteran, dan perangkat keamanan. Kompresi dibutuhkan untuk memudahkan penyimpanan dan transmisi tanpa kehilangan informasi secara signifikan. Tujuan utama kompresi video adalah untuk mengurangi ukuran file dan memaksimalkan kualitas rekonstruksi. Pada tesis ini, algoritma Geometric Wavelet (GW) digunakan untuk kompresi spasio-temporal video digital. GW merupakan kombinasi antara pohon Binary Space Partition (BSP) dengan pohon Geometric Wavelet. Metode BSP membagi citra atau frame secara rekursif dengan berorientasikan garis secara hirarkis. Pembagian rekursif ini menghasilkan sebuah pohon biner yang disebut sebagai representasi pohon BSP dari citra atau frame. Node-node pada pohon BSP yang terpilih sebagai node representatif membentuk representasi pohon GW. Metode GW ini terbukti mengurangi efek blocking pada hasil rekonstruksi video. Kualitas video diukur menggunakan parameter Peak Signal-to-Noise Ratio (PSNR) dalam satuan dB.
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Video is currently used in several different applications, such as video conferencing, medical diagnostics, and security devices. Compression is needed to facilitate both storage and transmission without loss of information. The main goal of video compression is to minimize file size while maximizing reconstruction quality. In this thesis, the Geometric Wavelet (GW) algorithm is applied to spatio-temporal digital video compression. It combines a Binary Space Partition (BSP) tree with a Geometric Wavelet tree. The BSP approach recursively partitions an image or frame using oriented lines in a hierarchical manner. This recursive partitioning generates a binary tree, referred to as the BSP tree representation of the image. Selected representative nodes within the BSP tree form the GW tree representation. The GW method effectively reduces blocking artifacts in video reconstruction. Video quality is evaluated using the Peak Signal-to-Noise Ratio (PSNR) parameter expressed in dB.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Video digital, kompresi video, wavelet, Binary Space Partition, Peak Signal to Noise Ratio , Digital Videol, video compression, wavelet, Binary Space Partiition, Peak Signal to Noise Ratio
Subjects:	Q Science > QA Mathematics > QA76.9.D33 Data compression (Computer science)
Divisions:	Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	magang .
Date Deposited:	29 Sep 2026 06:51
Last Modified:	29 Sep 2026 06:51
URI:	http://repository.its.ac.id/id/eprint/145019

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