一种基于图划分的人造红外目标实时分割算法

提出一种基于图划分的实时红外目标分割方法．选用规格化划分值作为区分目标和背景的最佳阈值选取的准则．该准则联合考虑了象素的灰度信息及其空间位置信息，因而分割红外目标比常规方法更为准确可靠．文章对该算法的时间复杂性及空间复杂性进行了分析，为满足实时处理的需要，对算法进行了简化处理，并定义四种方向的领域权值矩阵，提出一种快速查表的方法有效地解决了算法的实时性问题．试验结果表明，该方法能够有效地完成红外目标的准确分割，分割性能优干传统的Otsu准则和一维熵方法，同时，采用快速实现算法大大提高了该算法实时处理能力，节省了存储空间，从而使该算法在实际中能得到有效应用．

REAL-TIME SEGMENTATION TECHNOLOGY OF MAN-MADE INFRARED OBJECT BASED ON NORMALIZED CUTS

An effective aproach based on normalized cuts to segment infrared object was presented. The method is related to the graph theory. An image was represented as a weighted undirected graph, where the nodes of the graph were the pixels of the image, and an edge was formed between every pair of pixels. The weight on each edge was function of the similarity between the two pixels, and the similarity was related to the gray level and the position of pixels. Normalized cut was chosen as the principle to distingusish object from background. The time and space complexity of the algorithm was studied. Four kinds of domain-weight-matrix were defined and a quick table-search method was presented to improve the real-time algorithm. The experimental results show that the proposed method has excellence performance, and it is superior to the traditional segmentation method.