Current Issue Cover
基于能量累积与顺序形态滤波的经外小目标检测

叶斌1, 彭嘉雄1(华中科技大学图象识别与人工智能研究所,图象信息处理与智能控制教育部重点实验室,武汉 430074)

摘 要
针对红外序列图象中弱小目标的检测问题,提出了基于能量累积与顺序形态滤波的小目标检测方法,该方法通过设置一定大小的滑动窗口,对窗口内的图象序列进行能量累积,以达到去除图象中的随机噪声和提高目标的信噪比的目的,其目标检测采用由粗到精3个步骤,即首先利用顺序形态滤波抑制背景,并通过提取目标广义边缘来实现目标的粗定位,然后对可能存在目标的区域进行分割,通过提取目标几何特征来完成精确定位;最后利用序列图象中目标运动的连续性和轨迹的一致性来筛选出真正的目标,实验结果表明,该方法能有效地抑制背景和能提取目标广义边缘,并能通过自适应地选择分割门限来完成红外小目标的定位和检测。
关键词
Small Target Detection Based on Energy Accumulation and Order Morphology Filtering in Infrared Image

()

Abstract
Because of the influence of nature meteorological condition, background environment and the structures of objectors, detection of weak and small objectors in infrared image is one of difficulties among image objector detection and identification. A new small target detection method based on energy accumulation and order morphology filtering is presented for solving detection of moving small target with low SNR in infrared image sequence. Accumulating the energy of the image sequence in the sliding window with a setting size can remove the random noise in order to increase SNR. Three steps of target detection from coarse to fine are adopted. First suppressing background and extracting generalized edge of targets by using order morphology filtering, determining the prime location of the targets, then segmenting the regions where there are possible targets, extracting the geometrical features. Finally filtrating the true targets according to the principle of moving continuity and trajectory consistency of moving target in the image sequences. The experiments show that this method can effectively suppress background and extract generalized edge of targets, adaptively choose threshold for segment, perform the location and detection of small targets in infrared image.
Keywords

订阅号|日报