Optimization of Fractal Image Compression

TL;DR

This paper presents optimization techniques for fractal image compression, notably the Box Counting Method, to improve compression ratio and reduce computational time, making FIC more efficient.

Contribution

It introduces a novel, simple-to-integrate optimization approach for FIC that enhances both compression efficiency and speed.

Findings

Improved compression ratio and time with the new optimization techniques

The Box Counting Method effectively estimates fractal dimensions in FIC

Enhanced practical applicability of fractal image compression

Abstract

Fractal Image Compression (FIC) is a lossy image compression technique that leverages self-similarity within an image to achieve high compression ratios. However, the process of compressing the image is computationally expensive. This paper investigates optimization techniques to improve the efficiency of FIC, focusing on increasing compression ratio and reducing computational time. The paper explores a novel approach named the Box Counting Method for estimating fractal dimensions, which is very simple to integrate into FIC compared to other algorithms. The results show that implementing these optimization techniques enhances both the compression ratio and the compression time.