A COMPREHENSIVE GUIDE TO MULTIMEDIA APPLICATION OPTIMIZATION

Abstract

The escalating demand for computer animations, images, and video applications has underscored the significance of image and video compression. This paper addresses the imperative issue of image compression, with a focus on its pivotal role in data reduction and enhanced transmission speed. Two primary categories of image compression exist: lossy and lossless. Lossless compression maintains numerical fidelity with the original image, while lossy compression introduces controlled distortions. Various techniques, such as Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and fractal compression, fall under the lossy compression umbrella. Additionally, transform coding, Wavelet compression, Vector quantization, and more, contribute to the spectrum of image compression methods.

This study delves into the Fractal Compression approach, particularly Fractal Image Compression (FCI), which harnesses the self-replicating patterns in images. FCI creates a transformation that closely approximates the original image, preserving key features, and encodes the transformation parameters in a file. With a focus on natural images and their inherent similarities, FCI holds promise. In this paper, we offer an in-depth review of the FCI method, commencing with an introduction to fractals and their application in image compression. The presented analysis sheds light on the principles and potential of FCI in meeting the demands of contemporary image compression requirements.