本文選題：過采樣 + 目標檢測��； 參考：《國防科學技術大學》2015年碩士論文

【摘要】：紅外弱小目標檢測是目標檢測領域的一項重難點問題。由于弱小目標信噪比比較低,淹沒在背景和噪聲中,檢測難度大。本文研究了過采樣體制下的目標檢測算法。首先建立過采樣掃描紅外圖像模型,并分析了紅外弱小目標特性。其次介紹了幾種典型的背景抑制算法,并對空域高通濾波,均值濾波,最大中值濾波進行詳細的介紹。再次,用矩形結構元素及線性多結構元素形態(tài)學抑制背景,通過分析:線性多結構元素可以抑制云層背景邊緣,但無法消除小于目標的亮點噪聲,而矩形結構元素對云層背景邊緣抑制效果較差,但是可以消除小于目標的亮點噪聲。在此基礎上,利用過采樣圖像中目標的特點,結合線性多結構元素和矩形結構元素的優(yōu)點,提出了基于過采樣體制的形態(tài)學多級濾波背景抑制算法,并對結構元素進行最優(yōu)化構造。同時對該算法的結構及原理進行了具體地闡述,并通過仿真對算法進行分析。仿真實驗得出該算法在提高過采樣掃描圖像的信噪比方面效果是比較好的,而且候選目標點也比較少,算法的檢測能力明顯較高,在多幀檢測中,對傳統(tǒng)的鄰域判決法進行改進,提出基于聯(lián)合狀態(tài)估計的過采樣目標序列檢測算法,采用改進的算法對單幀檢測階段檢測出的目標進行軌跡檢測,改進的算法不僅檢測出了目標軌跡,而且虛警率也較低,同時驗證了單幀檢測中提出的基于過采樣體制的形態(tài)學多級濾波背景抑制算法是可行的。
[Abstract]:Infrared small and weak target detection is an important and difficult problem in the field of target detection. Because the signal-to-noise ratio of small target is low, it is difficult to detect because it is submerged in background and noise. In this paper, the target detection algorithm under oversampling system is studied. Firstly, the oversampling scanning infrared image model is established, and the characteristics of infrared dim targets are analyzed. Secondly, several typical background suppression algorithms are introduced, and the spatial high pass filter, mean value filter and maximum median filter are introduced in detail. Thirdly, the morphology of rectangular structure element and linear multi-structure element is used to suppress the background. Through analysis, the linear multi-structure element can suppress the edge of cloud background, but it can not eliminate the bright spot noise which is smaller than the target. The rectangular structure element has a poor suppression effect on the cloud background edge, but it can eliminate the bright spot noise which is smaller than the target. On this basis, taking advantage of the characteristics of targets in over-sampled images and combining the advantages of linear multi-structure elements and rectangular structural elements, a multi-level morphological filtering background suppression algorithm based on over-sampling scheme is proposed. The structure elements are constructed optimally. At the same time, the structure and principle of the algorithm are described in detail, and the algorithm is analyzed by simulation. The simulation results show that the algorithm is effective in improving the signal-to-noise ratio of the over-sampled scanned images, and the candidate target points are less, the detection ability of the algorithm is obviously higher, in the multi-frame detection, The traditional neighborhood decision method is improved, and an oversampling target sequence detection algorithm based on joint state estimation is proposed. The improved algorithm is used to detect the track of the target detected in single frame detection stage. The improved algorithm not only detects the trajectory of the target, but also has a low false alarm rate. At the same time, it verifies the feasibility of the multi-level morphological filtering background suppression algorithm based on over-sampling in single-frame detection.
【學位授予單位】：國防科學技術大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TP391.41;TN219

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本文編號：2036628