Image Sharpness Measure Using Eigenvalues

摘要：

This paper proposes a novel statistical approach to formulate image sharpness metric using eigenvalues.Statistical information of image content is represented effectively using a set of eigenvalues which is computed using Singular Value Decomposition (SVD).The approach is started by normalizing the test image with its energy to minimize the effects of image contrast.Covariance matrix which is computed from the normalized image is then diagonalized using SVD to obtain its eigenvalues.Sharpness score of the test image is determined by taking the trace of the first six largest eigenvalues.The performance of the proposed approach is gauged by comparing it with orthogonal moments-based sharpness metrics.Experimental results show the advantages of the proposed approach in terms of providing wider working range and more precise prediction consistency in noisy condition.

作者: Chong-Yaw Wee Raveendran Paramesran

作者单位: Dept.of Electrical Engineering,Faculty of Engineering,University of Malaya,50603 Kuala Lumpur,Malaysia.

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）