主分量分析在图像信号处理中的应用  

Research on Applications of Principal Component Analysis in Image Processing

作　　者：王军敏 芦荐宇 张诗梦 WANG Junmin;LU Jianyu;ZHANG Shimeng(School of Information Engineering, Pingdingshan University, Pingdingshan, Henan 467036, China)

机构地区：[1]平顶山学院信息工程学院,河南平顶山467036

出　　处：《平顶山学院学报》2020年第5期49-53,共5页Journal of Pingdingshan University

基　　金：河南省科技厅科技攻关项目(202102210331);平顶山学院中青年骨干教师项目;平顶山学院博士科研启动基金项目(PXY-BSQD-202004)。

摘　　要：利用照相设备获取的原始图像数据通常含有大量的冗余信息,不利于图像数据的传输、存储、表示和识别.采用主分量分析方法提取原始图像的主要特征,去除原始图像数据中的相关性和冗余信息;然后,将上述方法应用于图像信号处理,包括图像的倾斜校正、人脸识别和图像压缩,获得了良好的实验结果,拓展和深化了主分量分析方法在图像处理领域的应用.Original images acquired by camera usually contain a lot of redundant information,which is not convenient for transmission,storage,representation and recognition.To address the above problem,the principal component analysis is adopted to extract the main feature of the original images and remove redundant information.And then,the principal component analysis is applied to image processing,such as image tilt correction,image recognition,and image compression,and the good experimental results are obtained,which broadens and deepens the application of principal component analysis in the field of image processing.

关 键 词：主分量分析 图像倾斜校正 人脸识别 图像压缩 

分 类 号：TP391.413[自动化与计算机技术—计算机应用技术]