Research And Application Of Object Detection Based On Image Fusion

In recent years,image fusion has been an important and useful technique for image analysis and computer vision.The aim of image fusion is to combine multiple source image data from various sensors intelligently and to obtain more detailed,complete description and decision than any of the individual source images.As a result of this processing,the fused image is more useful for human and machine perception or further image processing tasks such as object detection and recognition.This thesis studies on techniques and applications of the multiple remote sensing image fusion.The thesis studies on the technique of aligning two images automatically and experiments show that it is feasible and effective.The thesis also discusses the evaluation criteria on the multiple remote sensing image fusion performance.These evaluation criteria are classified according to condition and purpose.The thesis analyzes the decomposition and reconstruction of gradient pyramid and puts forward a image infusion method based on different types of pyramids.The effects of the type of pyramid, the number of pyramid decomposition level,and the scheme of fusion to the fusion result were investigated.Because the targets of some images are dim or the background is too complicated,it is difficult to detect the targets of some images.In order to resolve the problem of dim target detection,a novel approach based on image fusion and mathematical morphology was proposed.It shows the importance and feasibility of image infusion technique.