Objective Evaluating Method to Fusion Image Quality Based on ANN
Research on quality evaluating of fusion images is meaningful to improve the registration technology and fusion algorithms. The objective assessment metrics based on fusion image itself can not show comprehensively the fusion image quality, which could be incongruent against human eye response. Provide a new assessment method for fusion image quality by means of building artificial neural network model. The metrics inculding mean value, standard deviation, gradient is choosed as the input neural cell. A hidden layer is designed to carry out assorting perfoemance. And the artificial neural network obtain the image quality assessing mapping functions and to classify the training samples into different types by means of the supervised learning. The experiment shows the noteworthy concordance between the simulation result and human eye response to identifying samples. Compared with single evaluation indexes, the new quality evaluation model can show effectively the subjective response of human eye to fusion image.
Fusion image artificial neural net evaluation
ZHANG Yong ZHANG Ling
Beijing Institute Technology University, School of Information Science and Technology Shijiazhuang, ShiJiaZhuang Mechanical Engineering College, Department of Electrical Engineering Shijiazhuang, Chin
国际会议
西安
英文
871-874
2010-08-07（万方平台首次上网日期，不代表论文的发表时间）