Change Vector Analysis using Enhanced PCA and Inverse Triangular Function-based Thresholding

Defence Science Journal

D. S. Negi¹  Munmun Baisantry¹  O. P. Manocha¹ 

[1] Defence Electronics Applications Laboratory, Dehradun

关键词: Change vector analysis;    principal component difference;    inverse triangular function;    Kauth-Thomas transformation;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: Defence Scientific Information & Documentation Centre

【 摘 要 】

Change vector analysis is a very sophisticated method to evaluate land-use/land-cover changes meaningfully. By making proper choice of input data in the form of bands (for instance, red, NIR etc) or features (for instance, greenness, brightness, wetness etc), information about both the magnitude as well as the type/nature of changes can be extracted. However, improper selection of thresholds is always a hindrance to a good change detection algorithm. The paper has proposed an improved technique to select threshold appropriately by means of principal component difference and inverse triangular function. The changes have been represented using class-based circular wheel representation. Results have been shown to further testify the performance of proposed algorithm. Defence Science Journal, 2012, 62(4), pp.236-242 , DOI:http://dx.doi.org/10.14429/dsj.62.1072

【 授权许可】

Unknown