基于二維概率密度函數(shù)比較的SAR圖像變化檢測(cè)方法
doi: 10.11999/JEIT141140
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61302194)資助課題
SAR Images Change Detection Based on Comparison of Two-dimensional Probability Density Functions
-
摘要: 該文將傳統(tǒng)區(qū)域統(tǒng)計(jì)分布特征變化檢測(cè)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(cè)方法。該方法首先將觀測(cè)區(qū)域內(nèi)相鄰像素的灰度值組合成2維觀測(cè)矢量，而后采用2維Gram- Charlier展開(kāi)式對(duì)觀測(cè)矢量在不同時(shí)相圖像中的2維概率密度函數(shù)分別進(jìn)行估計(jì)，在此基礎(chǔ)上，借助K-L散度理論對(duì)2維概率密度函數(shù)在不同時(shí)相圖像間的變化大小進(jìn)行定量分析以實(shí)現(xiàn)變化檢測(cè)。實(shí)驗(yàn)結(jié)果表明，與傳統(tǒng)方法相比，該文方法具有更優(yōu)的檢測(cè)性能。
-
關(guān)鍵詞:
- 合成孔徑雷達(dá) /
- 圖像變化檢測(cè) /
- 概率密度函數(shù)估計(jì)
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
-
計(jì)量
- 文章訪問(wèn)數(shù): 1644
- HTML全文瀏覽量: 209
- PDF下載量: 566
- 被引次數(shù): 0
下載:
