红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2013年
9期
2566-2573
,共8页
龚俊亮%何昕%魏仲慧%朱弘%郭立俊
龔俊亮%何昕%魏仲慧%硃弘%郭立俊
공준량%하흔%위중혜%주홍%곽립준
红外图像%尺度空间%目标检测
紅外圖像%呎度空間%目標檢測
홍외도상%척도공간%목표검측
infrared image%scale-space theory%targets detection
为了检测红外场景中尺寸大小变化的弱小目标,针对传统滤波方法中固定大小滤波核对此类特性目标检测表现出的不足,提出一种基于尺度空间理论的红外弱小目标检测方法。首先对弱小目标特性进行分析,提出采用点扩散函数形式的目标模型来描述弱小目标;采用固定自适应邻域的方法对原始红外图像进行预处理,抑制背景杂波,增强目标能量;依据尺度规范化后的拉普拉斯尺度空间对图像不同元素滤波响应的不同,获取图像中的可疑目标,利用可疑目标点与其周围像素的梯度关系得到可疑目标点的中心坐标,并据此得到其在图中的尺寸大小;对每个可疑目标划分一个自适应大小窗口,获取分割阈值,分割出真实目标。实验结果表明,该方法能较好地检测出弱小目标,且具有较低的虚警率。
為瞭檢測紅外場景中呎吋大小變化的弱小目標,針對傳統濾波方法中固定大小濾波覈對此類特性目標檢測錶現齣的不足,提齣一種基于呎度空間理論的紅外弱小目標檢測方法。首先對弱小目標特性進行分析,提齣採用點擴散函數形式的目標模型來描述弱小目標;採用固定自適應鄰域的方法對原始紅外圖像進行預處理,抑製揹景雜波,增彊目標能量;依據呎度規範化後的拉普拉斯呎度空間對圖像不同元素濾波響應的不同,穫取圖像中的可疑目標,利用可疑目標點與其週圍像素的梯度關繫得到可疑目標點的中心坐標,併據此得到其在圖中的呎吋大小;對每箇可疑目標劃分一箇自適應大小窗口,穫取分割閾值,分割齣真實目標。實驗結果錶明,該方法能較好地檢測齣弱小目標,且具有較低的虛警率。
위료검측홍외장경중척촌대소변화적약소목표,침대전통려파방법중고정대소려파핵대차류특성목표검측표현출적불족,제출일충기우척도공간이론적홍외약소목표검측방법。수선대약소목표특성진행분석,제출채용점확산함수형식적목표모형래묘술약소목표;채용고정자괄응린역적방법대원시홍외도상진행예처리,억제배경잡파,증강목표능량;의거척도규범화후적랍보랍사척도공간대도상불동원소려파향응적불동,획취도상중적가의목표,이용가의목표점여기주위상소적제도관계득도가의목표점적중심좌표,병거차득도기재도중적척촌대소;대매개가의목표화분일개자괄응대소창구,획취분할역치,분할출진실목표。실험결과표명,해방법능교호지검측출약소목표,차구유교저적허경솔。
In order to detect small targets with changing size in infrared scene, aiming at the problems in traditional filtering method with fixed size filter, a method for small and dim infrared targets detection based on scale-space theory was proposed. First, the target characteristic was analyzed and point spread function form was used to represent the target model. Then, in order to suppress background clutter and enhance the power of target, fixed adaptive neighborhood method was used in image preprocessing, on the basis of Laplace scale-space after scale standardization which has different filtering responses for different elements, the suspicious targets were obtained in the images, then with the gradient relationship between suspicious target point and its surrounding pixels, the coordinates of the suspicious targets centers and its size were got; Finally, each suspicious targets gained an adaptive window to obtain segmentation threshold and true targets. Experiments results show that, compared with traditional methods, the new method proposed in this paper has a better performance to detect small targets, and has a lower false alarm rate.