摘要
针对图像占用空间大,特征表示时维数较高等的缺点,系统介绍了主成分分析(PCA)的基本原理。提出了利用PCA进行图像数据压缩与重建的基本模型。实验结果表明,利用PCA能有效的减少数据的维数,进行特征提取,实现图像压缩,同时并根据实际需要重建图像。
Point to the weakness of space-consuming and higher dimension when featuring the images of the traditional method, the article introduced the basic principles of principal component analysis （PCA）, established a basic model of a image data compression in use of PCA. Experimental results show that PCA can effectively reduce the data dimension, implement feature extraction, realize the image compression, and reconstruct image to meet the actual needs.
出处
《电子设计工程》
2012年第5期126-128,共3页
Electronic Design Engineering
基金
西安工业大学校长基金(XGYXJJ0529)
关键词
图像压缩
PCA
图像重建
特征提取
image compression
Principal Components Analysis
image reconstruction
feature extraction
