Image compression is a common data compression technology that can reduce the storage space of image files and improve transmission efficiency. Fractal coding is a method for image compression that is based on fractal theory and achieves compression by finding and utilizing self-similarity within the image. In this article, we will introduce how to use Matlab to implement image compression based on fractal coding and provide the corresponding source code.
The basic principle of fractal coding image compression is to use local self-similarity in the image to reconstruct the entire image. Specifically, fractal coding divides an image into many small blocks and then achieves compression by looking for similarities between these small blocks. Each of these patches can be viewed as a local pattern of the image, called a "fractal code." Compression of the image is achieved by finding areas in the image that best match these fractal codes and replacing them with the corresponding codes.
The following is an example code for using Matlab to implement image compression based on fractal coding:
% 读取输入图像
inputImage = imread('input_image.jpg');
% 将图像转换为灰度图像
grayImage = rgb2gray(inputImage