Research And Application Of Wavelet Transformation On Ultrasonic Image Processing

Medical ultrasound imaging technology occupies an important position in today's advanced medical imaging technology. However, defect in medical ultrasonic images is some unique speckle noise, making the medical staff in the diagnosis and treatment difficult. This makes the ultrasound image must be reduced noise and enhancement. The research direction is the wavelet transform in image de-noising and image enhancement. Wavelet transform for image de-noising and enhancement has obvious advantages over the traditional image de-noising and image enhancement method is more effective.The development of medical ultrasound, the principle of ultrasound images and ultrasound imaging equipment components are briefly introduced. Ultrasound medical images on the existing de-noising algorithm is studied, including image averaging, neighborhood average, median filtering and low pass filter. Based on the theory of wavelet transform, this thesis proposes image de-noising algorithm based on wavelet transform. First, select the appropriate wavelet function to multiple scale image decomposition, the decomposed high frequency coefficients quantify the threshold, and finally the low-frequency coefficients and the processed wavelet reconstruction layers of high-frequency coefficients.Study the image enhancement based on wavelet transform, the first analysis of the basic method of image enhancement including the gray level transformation, histogram equalization and high pass filtering, and then put image enhancement into the wavelet domain, and using the nonlinear gain function to enhance the high frequency coefficients, it can be effective while meeting the purpose of image de-noising and enhancement. Using MATLAB as a platform to achieve the process of image de-noising and enhancement algorithms, and the corresponding image processing results are analyzed and compared to verify the feasibility and efficiency of wavelet de-noising and enhancement.