Multiresolution Segmentation Of Noise Image Based On Wavelet Transform

The basic principle of multiresolution Segmentation of noise image is suppressing noise. Multiresolution analysis makes use of the independent information in different resolution. Mallat combines wavelet analysis with multiresolution analysis, and multiresolution analysis based on wavelet transform becomes a focal field.Wavelet analysis has been a new field in recent years. It has been accepted as a very important breakthrough of Fourier analysis, and has become a useful tool in image and signal processing. We have study the fundamental theory of Wavelet transform, and then we explore the application of multiresolution analysis based on Wavelet Transform in noise image segmentation. Through comparing between classical image segmentation algorithm and Multiresolution Analysis based on Wavelet Transform, we can know the excellence of Multiresolution Analysis.Suppressing noise is the difficult problem in image segmentation, so we have study suppressing noise in multiresolution segmentation based on Wavelet transform. To discern edge and noise in multiresolution edge detection used single threshold, we put forward a kind of adaptive threshold and improve the method of edge linking.Median filter is a kind of nonlinear filter, and it has good abilities of keeping edge. A new kind of adaptive fuzzy median filter defined by Boolean function is given in this paper, and this method can keeping edge very well and reduce noise at the same time.Gas-liquid image in chemistry reaction has close object and lower signal-to-noise ratio, so gas-liquid image segmentation is very difficult. In 2-D grey-wavelet transform distribution, the Euclidean distance between background, object and edge is very far, so we can carry out image segmentation using this character. We describe a kind of method combing wavelet transform and fuzzy cluster, and succeed in gas-liquid image segmentation.