基于FFT和PCA的图像压缩方法研究  

Research on Image Compression Method Based on Fast Fourier Transform and Principal Component Analysis

作　　者：苗水清 闫文耀[1] 张静[1] 吴梦蝶 MIAO Shuiqing;YAN Wenyao;ZHANG Jing;WU Mengdie(Xi'an Innovation College of Yan'an University,Xi'an 710100,China)

机构地区：[1]延安大学西安创新学院,陕西西安710100

出　　处：《佳木斯大学学报（自然科学版）》2022年第3期29-32,共4页Journal of Jiamusi University：Natural Science Edition

基　　金：延安大学西安创新学院校级项目(2019XJKY-1);陕西省教育厅项目(21JK0997);陕西省教育厅新工科项目(陕教[2020]75号)。

摘　　要：图像压缩作为数字图像处理研究与应用的重要技术,目的在于通过编码或者提取主要成分以压缩图像数据量,在图像文件传送以及图像的快速处理研究领域有重要意义。文中采用快速傅里叶变换(FFT)将图像转换到频域,并应用主成分分析法(PCA)对频域图像进行降维处理以实现图像压缩,最后通过PCA逆变换和FFT逆变换实现图像重构,实验结果表明该方法对图像的压缩效果较好,对图像噪声能起到抑制作用,且还原效果较好。Image compression as an important technology for digital image processing research and application,the purpose is to encode or extract the main components to compress the amount of image data.It is of great significance in the field of image file transfer and fast processing of images.In this paper,fast Fourier transform(FFT)is used to convert the image to the frequency domain,and the principal component analysis(PCA)is used to reduce the dimension image in frequency domain image to realize image compression.Finally,PCA inverse transform and FFT inverse transform are used to reconstruct the image.The results of Matlab simulation show that the method has better compression effect on the image,and can not only suppress the image noise,but also has better reduction effect.

关 键 词：图像压缩 FFT PCA 数字图像 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]