Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JOIV : International Journal on Informatics Visualization
Hasoon, Jamal N.
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOIV : International Journal on Informatics Visualization

 1 
Video Compression Using Quadtree Decomposition and Bitplane Coding Mahdi, Sura Hameed; Aziz Sahy, Seba; Hasoon, Jamal N.
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.3172

Abstract

Due to the exponential rise in multimedia content, video files now make up a large amount of internet traffic and data storage requirements. Video compression is essential for reducing video data storage and transmission bandwidth, as it involves processing frames before they are transmitted or stored. High-resolution formats offer enhanced viewing experiences but result in enormous file sizes, posing challenges related to storage, bandwidth consumption, and transmission efficiency. This paper aims to address these challenges by developing a novel video compression algorithm that optimizes the balance between file size reduction, processing speed, and visual quality preservation. This method requires intensive computation, especially for video frames, and the image compression equipment is highly complex and expensive in terms of hardware. In this paper, an efficient method for video compression is proposed by combining several techniques, including quadtree, bitmap coding, and DCT. The video files are divided into scenes, which are further categorized into two types of frames: keyframes and related frames. The keyframes are segmented by the quadtree decomposition method into three region types (small block, medium block, and large block). The small block is compressed using bitmap coding (lossless compression), the medium block is compressed using DCT techniques, and the large block (that has fewer details) is compressed by replacing the mean of the color RGB values. All blocks are merged into a compressed file with the location of each block for decompression. The proposed method achieves an accurate compression result of approximately 17% from the input video size and can be extended to be combined with other methods.
Co-Authors Aziz Sahy, Seba Mahdi, Sura Hameed