Mathematical Morphology In Sar Image Processing

Speckle,appearing in synthetic aperture radar (SAR) images as granular noise ,is generated by the coherent processing of radar signals.It severly affects the image qualities.To alleviate deleterious effects of speckle without blurring edge and fine detail.But most algorithms cannot satisfy these two demands very good.In this article,it first analyzes the principle of speckle forming,discusses the noise model and the fundamental properties of speckle in SAR images.It then discussed several well-known speckle filtering algorithms in detail .this paper improves the filtering algorithms based on mathematical morphology .Tests are performed on real SAR images.A set of performance criteria is established and comparisons are made between the improved algorithm and the geometric fitler as well as the Lee filter etc..Result shows the improved algorithm suppresses the speckle while at the same time preserves the edges and fine detail relatively.Edge detection is one of the base contents on image processing and analysis,on which people have not as yet find a satisfactory way out.The edge which is one of the most important fundamental feature of an image,embodying the other features such as position and outline etc.,is widely used in image analysis and processing such as feature description,image segmentation,image enhancement,pattern recognition and image compression etc.,So edge detection is the research hotspot in the technology of image processing and analysis all the while,on which the new theory and methods are put forward constantly. Currently there are a lot of methods such as Robert function,Sobel function,and Laplacian function .But all these algorithms are based on the average of neighborhoods.So after processing,the edge of image is dim,and the image affects our version,in this paper a new improved edge detection algorithm based on mathematical morphology is offered.Mathematical morphology founded on set theory is a new method pplied in the field of image processing and pattern recognition.Its prime principle is using a certain structuring element to measure and extract the corresponding form in an image so that we can analyze and recognize the image.Edge detection plays a special role in image processing and computer vision.It is one of the most important links in the basic vision processing.The edge detection processing based on mathematical morphology excels that based on differential operation.It is not so sensitive to noise as differential operation and the extracted edge is smoother.It can not only embody the set characteristics of an image and efficiently detect the edge but also meet the real-time expectations.At the same time,it can reduce the noise by changing morphological scale.The experiment result demonstrates that the edge detection algorithm has a good performance of noise reduction and real-time compared with traditional edge detectors,and the detected edge is smooth,and it is simple.So this method has its practicability.