Wavelet Based Image Coding Schemes : A Recent Survey

TL;DR

This survey reviews recent wavelet-based image coding techniques, highlighting their advantages in reducing artifacts and improving energy compaction, and discusses various algorithms and their development for enhanced image compression.

Contribution

It provides a comprehensive overview of recent wavelet image coding algorithms, comparing their features, and offering insights for future development and implementation.

Findings

Wavelet schemes reduce blocking artifacts compared to JPEG.

Wavelet algorithms achieve superior energy compaction and high-quality images.

The survey discusses recent advancements like GW coding and optimized algorithms.

Abstract

A variety of new and powerful algorithms have been developed for image compression over the years. Among them the wavelet-based image compression schemes have gained much popularity due to their overlapping nature which reduces the blocking artifacts that are common phenomena in JPEG compression and multiresolution character which leads to superior energy compaction with high quality reconstructed images. This paper provides a detailed survey on some of the popular wavelet coding techniques such as the Embedded Zerotree Wavelet (EZW) coding, Set Partitioning in Hierarchical Tree (SPIHT) coding, the Set Partitioned Embedded Block (SPECK) Coder, and the Embedded Block Coding with Optimized Truncation (EBCOT) algorithm. Other wavelet-based coding techniques like the Wavelet Difference Reduction (WDR) and the Adaptive Scanned Wavelet Difference Reduction (ASWDR) algorithms, the Space Frequency Quantization (SFQ) algorithm, the Embedded Predictive Wavelet Image Coder (EPWIC), Compression with Reversible Embedded Wavelet (CREW), the Stack-Run (SR) coding and the recent Geometric Wavelet (GW) coding are also discussed. Based on the review, recommendations and discussions are presented for algorithm development and implementation.