Automatic Detection of Aerial Vehicle in Cloudy Environment by Using Wavelet Enhancement Technique

Automatic target detection of surface to air surveillance and tracking systems in video applications is an important issue, because it is the first step for track initiation and continuity. Target detection can be readily overcome for clear sky conditions, but it may be a complicated problem for cloudy sky conditions. In order to fulfill automatic target detection by using conventional image processing techniques may be a hard problem in cloudy sky conditions and improper light affects. The difficulty comes from the clutter rates stem from clouds, and the target may get lost in the clutters that occupies in the whole frame area. In order to increase the detection possibility background clutters should be eliminated by using image processing techniques frame by frame. In this work a novel approach is proposed to detect air vehicles in every kind of cloudy sky conditions. For this purpose a wavelet based image enhancement algorithm is implemented to the video frames, then conventional techniques are used. These conventional techniques are the reciprocal pixel intensity measurement data usage, Sobel operator and thresholding processes for edge detection. The proposed algorithm gives outstanding results for flying object detection in different sky conditions