Color Compression of RGB Image Based on K-means Clustering

摘要：

　　In life, the amount of information in an image is often very large. Color images usually contain thousands of colors, which brings great inconvenience to peoples storage and transmission efficiency. Therefore, the image compression method is gradually being viewed by all. Under the premise of lossy compression, this paper focuses on the influence of RGB image before and after color compression on absolute mean error, establishes K-means clustering model, randomly selects the initial clustering center, and performs image color compression.

关键词： K-means clustering method initial clustering center color compression

作者: Mudan Lv Xiao Wang Yining Xue Li Yu Mingjie Jin

作者单位: Nanchang Institute of Science & Technology, Nanchang, China Donghua University, Shanghai, China Beijing Forestry University, Beijing, China Dongbei University of Finance and Economics, Dalian, China Hangzhou Dianzi University, Dalian, China

会议类型: 国际会议

会议名称: 2019 6th International Conference on Machinery, Mechanics, Materials and Computer Engineering (MMMCE 2019)(2019 第六届机械、材料和计算机工程国际会议)

会议地点: 呼和浩特

会议语种:英文

页码: 760-768

在线出版日期: 2019-07-27（万方平台首次上网日期，不代表论文的发表时间）