基于二維概率密度函數(shù)比較的SAR圖像變化檢測方法
doi: 10.11999/JEIT141140 cstr: 32379.14.JEIT141140
基金項目:
國家自然科學基金(61302194)資助課題
SAR Images Change Detection Based on Comparison of Two-dimensional Probability Density Functions
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摘要: 該文將傳統(tǒng)區(qū)域統(tǒng)計分布特征變化檢測方法拓展到2維特征空間，提出一種基于2維概率密度函數(shù)比較的SAR圖像變化檢測方法。該方法首先將觀測區(qū)域內相鄰像素的灰度值組合成2維觀測矢量，而后采用2維Gram- Charlier展開式對觀測矢量在不同時相圖像中的2維概率密度函數(shù)分別進行估計，在此基礎上，借助K-L散度理論對2維概率密度函數(shù)在不同時相圖像間的變化大小進行定量分析以實現(xiàn)變化檢測。實驗結果表明，與傳統(tǒng)方法相比，該文方法具有更優(yōu)的檢測性能。
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關鍵詞:
- 合成孔徑雷達 /
- 圖像變化檢測 /
- 概率密度函數(shù)估計
Abstract: In this paper, the tradition change detection method based on local statistical feature is expanded to two-dimensional feature space, and a SAR image change detection method based on comparison of two-dimensional probability density functions is proposed. In this method, the values of adjacent pixels are combined to build two-dimensional observation vector. Then, in each temporal image, the Probability Density Function (PDF) of the vector is estimated by two-dimensional Gram-Charlier expansion. On the basis, change detection is fulfilled by computing the K-L divergence between the PDFs in different temporal images. Experiment results show that the proposed algorithm has better performance than the traditional method.-
Key words:
- SAR /
- Image change detection /
- Estimation of probability density function
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