Wavelet Analysis In The Application Of De-noising And Enhancement Of Medical Ultrasound Image

Wavelet transform is a nee signal and image processing tool developed in recent years. The wavelet analysis has excellent time and frequency feature, which hand a progmising application in image de-noising and enhancement, it make the field full of vitality force.Ultrasonic detection technology has already been one of the important means of medical clinical diagnosis. Noise derived from the imaging degraded image quality and affected the detection rate of correctness. So noise must be removed from ultrasound image and enhance image should be enhanced.Ultrasound image de-noising and enhancement are a pre-processing step in its processing, it is also the premise of disease recognition and analysis. Research on ultrasonic image de-noising and enhancement have important meaning. At first the present state of research on de-noising and enhancement based on wavelet are introduced in this paper, then we make a brief description of theoretical knowledge about image de-noising and enhancement via wavelet. Finally, both image de-noising and enhancement based on wavelet are mainly studied according to multi-resolution of wavelet analysis together with human vision, we proposed relevant methods. The contents are as follows:â’ˆ In the aspect about noise removal of ultrasound image, we present wavelet de-noising methods based on Bayesian estimation and semi-soft threshold image de-noising. The two methods, we make different processing in diverse resolution of image. The method of semi-soft threshold embody the idea of multi-resolution together with adaptive process. Experiment result shows that the two methods can preserve some useful image edge and details to doctor as much as possible while removing noise, it also indicate that the two are simple and reliable.â’‰ In the aspect of ultrasound image enhancement. Two methods are presented. The first method is of high components strengthened based on wavelet to enhance image detail, then, image vision quality is improved through nonlinear contrast enhancement. The second one via wavelet together with fuzzy algorithm. The two methods not only enhance image details but also fit in with human vision, distinct of image is improved and noise over-enhancing can be voided in flatness area. The experiment results indicate that they have worthiness in practical application.