Research And Application Of Image Edge Detection Algorithm Based On Wavelet And Morphology

Edge Character is one of the most important features of image. The edge whichcontains large amounts of important fundamental feature of an image, including thelocation of the image and outline Characteristics etc., is widely used in image analysisand processing such as feature description, image segmentation, image enhancement,pattern recognition and image compression etc., So edge detection has a veryimportant position in digital image processing, How to quickly and accurately extractthe edge of the image has become the key topic and the difficult problem whichPeople have been concerned and researched.There are many methods for image edge detection. The traditional edge detectionoperators have Roberts operator, Sobel operator, Prewitt operator, Laplacian operator,LOG operator and Canny operator, We commonly use wavelet transform andmathematical morphology in the application of edge detection. In order to improve theeffect of the edge detection, this paper uses a kind of wavelet analysis andmathematical morphology method to extract the new combination of image edge.Because wavelet transform has good time-frequency localization characteristics andmultis-cale analysis ability, which can be used to can detect the dispersion-decreasingedge namely Laplace domain shape and roof edges in the small scales, and identifythe dispersion-decreasing edge in the larger scales, but also has a natural antinoisecharacteristics which is not sensitive to noise. The basic idea of mathematicalmorphology is to use certain shape and structure elements to measure and extractingimages of image and corresponding shape, which makes analysis and recognitionmathematical morphological edge detection method can effectively remove the noiseand protect details, but also has a operation simple, may parallel computing and easyto hardware implementation, etc. This paper researches the application ofmathematical morphology and wavelet method in edge detection. And the wavelettransform and mathematical morphology edge detection features combination isapplied to image edge detection, in order to obtain good edge detection effect.Firstly, this paper introduces the definition of image edge and the steps of edgedetection, and the detailed introduces the principle of the traditional edge detection operators, analyzes the performance,advantages and disadvantages of all kinds ofoperators, and validates it in the experiment. We then mainly introduces the basictheory of the image decomposition and reconstruction of the wavelet transform andthe basic principle based on multi-scale wavelet transform modulus maxima methodapplied to detect edge, gives the detailed steps of the algorithm for edge detection andfusion. This paper also introduces the basic theory of mathematical morphology,mainly studies the core factor (structural elements), gives two kinds of improvedstructural elements, and has been proved by simulation experiment. Finally thewavelet transform respectively combined with two kinds of improved morphologicaloperators, constitutes the two new hybrid algorithms, and its application in seismicfault fracture edge detection has been achieved good results.