Preprocessing of Colour Images Based on the Principal Components Analysis
PCA can be thought as technique that takes a collection of data and transforms it such that the new data has given statistical properties. The statistical properties are chosen such that the transformation highlights the importance of data elements. Thus, the transformed data can be used for classification by observing important components of the data. Data can also be reduced or compressed by eliminating (filtering out) the less important elements. In this paper we used PCA method to reduce RGB colour images to grey level in the preprocessing step. Two images were tested in the experiment. The first principal component was used as the grey level of the image in the experiment. The results show that the method is valid. The grey level can be used in the further processing and will be widely used in the image processing and computer vision and relatively field.
Preprocessing Colour Image Grey Level Principal Components Analysis(PCA)
Yang Yang Xiuqin Wang Di Zhang
School of Engineering, Bohai University, Liaoning Jinzhou, 121013, China School of Information Science and Technology, Bohai University, Liaoning Jinzhou, 121013, China Liaoning Datang international Jinzhou power generation Co.,ltd, Liaoning Jinzhou, 121001,China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
665-668
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）