Infrared Image Pseudo-Color Enhancement Based on Clustering Algorithm
Xiaohui Chang · Laser & Infrared · 2007
A new infrared image pseudo-color enhancement algorithm is presented based on K-means clustering.This method firstly does the statistic learning of the gray pixels in the original infrared image in order to create the initial cluster centers.Secondly,the data of gray in the original image are clustered by K-means with the initial cluster centers.Lastly,the infrared image is self-adaptively enhancement according to the result of clustering and the pseudo-color encoding separated into several sections.The experimental results indicate that this method could further improve the detail information,arrangement,and visual effect.