Color Correction Based on SIFT and GRNN for Multi-view Video

摘要：

In order to correct color differences between different views, a color correction method based on Scale Invariant Feature Transform (SIFT) and Generalized Regression Neural Network (GRNN) is proposed. Image features of the target image and source image are firstly extracted by SIFT algorithm. The value of these corresponding image points is used to construct the GRNN neural network that corrects the image color. Experimental results show that the proposed method can produce better correction result than histogram match. It also shows that the color differences between multiview video can be effectively solved by GRNN network.

关键词： color correction multi-view SIFT GRNN

作者: Chaohui Lu Yibing Zhang Yinghua Shen

作者单位: School of Information Engineering, Communication University of China, Beijing, 100024, China

会议类型: 国际会议

会议名称: The Fourth International Joint Conference on Computational Science and Optimization(第四届计算科学与优化国际大会 CSO 2011)

会议地点: 昆明、丽江

会议语种:英文

页码: 857-860

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）