本文選題：紋理上下文特征 + 統(tǒng)計流形　； 參考：《系統(tǒng)工程與電子技術》2017年10期

【摘要】：基于統(tǒng)計流形理論并結合形狀上下文思想,提出了能夠描述圖像紋理目標的紋理上下文特征,進而實現(xiàn)對遙感圖像紋理目標的識別。首先將圖像的灰度概率密度函數(shù)看作統(tǒng)計流形上的點,用所得到的圖像統(tǒng)計流形模型來描述圖像的紋理上下文特征;然后使用Fisher信息距離來度量流形上點之間的相似度,并利用匈牙利算法來匹配紋理上下文特征;最后通過計算匹配距離來實現(xiàn)不同圖像目標的相似性度量。實驗表明,與經(jīng)典的灰度共生矩陣、局部二值模式和統(tǒng)計流形算法相比,對于具有紋理特征的遙感圖像,該方法具有更高的識別率且具有普適性和穩(wěn)健性。
[Abstract]:Based on the statistical manifold theory and the idea of shape context, this paper proposes a texture context feature which can describe the texture object of the image, and then realizes the recognition of the texture object in the remote sensing image. Firstly, the gray level probability density function of the image is regarded as the point on the statistical manifold, and the image statistical manifold model is used to describe the texture context feature of the image, and then the similarity between the points on the manifold is measured by using the Fisher information distance. The Hungarian algorithm is used to match the texture context, and the matching distance is calculated to measure the similarity of different image objects. Experiments show that compared with classical gray level co-occurrence matrix, local binary pattern and statistical manifold algorithm, this method has higher recognition rate, universality and robustness for remote sensing images with texture features.
【作者單位】： 西北工業(yè)大學理學院;
【基金】：國家自然科學基金(61301196) 國家級大學生創(chuàng)新創(chuàng)業(yè)訓練計劃(201610699329)資助課題
【分類號】：TP751

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1 熊勇;路文初;劉繼忠;胡上序;;旋轉曲面變換PSO算法估計紋理圖像MRF參數(shù)[J];江南大學學報;2005年06期

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本文編號：1966579