Image Denoising And Edge Detection Of The Method Basing On Wavelet Theory

In Image processing, Image segmentation as an extremely important aspect of the image analysis and understanding to achieve the foundation. However, image acquisition, transmission and storage process for various reasons, tend to introduce noise, thus reducing the quality of image segmentation. Therefore, how to reduce image noise, image segmentation has become an important task.. The edge of the image contains a large number of worthy goals boundary information to identify the edge of the image is called edge detection. Edge detection is an important basis for image segmentation and a segmentation algorithm theme.Wavelet analysis is an effective analysis tool, wavelet theory with the continuous development and improvement of wavelet theory has been more and more applications to image denoising and edge detection. This paper puts forward a combination of wavelet transform and adaptive noise reduction filter wavelet transform and mathematical morphology edge detection method of integration.This began to wavelet theory, the traditional Image noise reduction methods, commonly used edge detection methods and morphology is described in detail. And the new noise reduction method and the edge detection method are compared with the traditional method. Wavelet transform and adaptive median filter method of combining wavelet transform to overcome the weak ability of the salt and pepper noise and median filtering of Gaussian noise on the shortcomings of weak will effectively combine the advantages of the two methods together. In the last, In addition to Gaussian noise and salt and pepper are well preserved while the image edge features than the traditional method of Image Noise Reduction. Based on wavelet transform and mathematical morphology edge detection algorithm, this method uses wavelet multi-resolution analysis and noise suppression ability of the features and mathematical morphology edge detection method can maintain smooth continuous edge features than the traditional test the edge obtained by fine and good continuity.