Review of Static Image Compression Algorithms

With the increasing development of digital image communication technology, the requirements for image quality, such as texture details, color levels, and dynamic range, are gradually increasing. This presents unprecedented challenges to the tradeoff between the reliability and effectiveness of image...

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Bibliographic Details
Published in:IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Online) Vol. 7; pp. 222 - 231
Main Authors: Liang, Yanxia, Jia, Tong, Li, Na, Liu, Xin, Jiang, Jing, Lu, Guangyue, Zhao, Meng
Format: Conference Proceeding
Language:English
Published: IEEE 15.03.2024
Subjects:
DCT coding
Discrete wavelet transforms
DWT coding
Heuristic algorithms
Image coding
image compression
Image processing
Image quality
JPEG
Prediction algorithms
predictive coding
Steganography
ISSN:2689-6621
Online Access:Get full text
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Summary:With the increasing development of digital image communication technology, the requirements for image quality, such as texture details, color levels, and dynamic range, are gradually increasing. This presents unprecedented challenges to the tradeoff between the reliability and effectiveness of image compression technology. Static image compression standards are an integration of phased research achievements in image compression algorithms and provide guidance for the study of image compression. Firstly, static image compression algorithms are introduced in three types: discrete cosine transform (DCT) coding-based methods, prediction coding-based methods, and discrete wavelet transform (DWT) coding-based methods, based on the existing literatures and the latest achievements. The basic idea is elaborated for each typical algorithm. Secondly, the advantages and disadvantages of these algorithms are analyzed, compared, and summarized. Thirdly, research on static image compression in the past three years is detailed and analyzed, which is divided into three technical fields: image steganography, high fidelity image processing, and optimization of image processing performance. Finally, the challenges in each field are proposed as well. Some potential future research work is advised.
ISSN:2689-6621
DOI:10.1109/IAEAC59436.2024.10503622