Research On The System Of Medical Image Enhancement Based On Wavelet Translate

Along with the grown of digital imaging technology, the digital image processingtechnology has become one of the important means of computer-aided detection andcomputer aided diagnosis. Medical image enhancement technique is not only thefoundation of medical image processing, but also an important research subject ofmedical image processing and analysis. Image enhancement technique is widely usedin the field of medical image diagnosis. The purpose of the image enhancementtechnique is to improve the image visual effect, to prove the image resolution and tomake it more suitable for the analysis of the machine processing or the visualcharacteristic of human. The image enhancement technique can help selectoutstanding focal point in order to provide reliable basis to pathological diagnosis andclinical diagnosis. The medical image enhancement has existed common problemswith general enhancement. At the same time the medical image is often to appear poorimage visual because of the influence of the imaging principle of kinds of medicalimaging and equipments. The most outstanding performance of medical image is thatthe contrast of grey level is low. The doctor can’t get a correct diagnosis due to lowcontrast of the details of focal point. The method of general image enhancement can’tget a good effect in medical image processing, therefore to seek an effective medicalimage enhancement has become one of the research hotspot in the field of the medicalimage processing.The quality of the medical image is influenced by the generation of noise in alarge extent. Especially the different medical image have different characteristics ofthe noise due to the different imaging principle. Therefore the main point of researchof medical image enhancement processing is to remove the noise and to improve theimage contrast. This paper has studied in the algorithm and the key technology ofmedical image enhancement technique and image enhancement system, whichincluding the research of image denoising, image enhancement and imageenhancement system. The specific is as the following:(1) According to the Gaussian noise characteristics of the CT image, combiningthe modified wiener filtering with the wavelet packet transform denoising method, a image denoising method based on the modified wiener filtering and wavelet packettransform is proposed which is used to remove additive Gaussian white noise. Theexperimental results show that the proposed denoising method can keep the edgeinformation of the image better and improve the visual quality of image effectively.(2) According to the characteristics of speckle noise of the ultrasonic image, onthe analysis of the principle of the wiener filtering and the characteristics of pulsecoupled neural network model, combining with wavelet transform method, a waveletadaptive denoising method based on the PCNN(W-PCNN-WD) is proposed. Theresult shows that the proposed filtering method is better than the other filteringmethods, and the effect is obvious. The method can keep the edge details of theinformation on the basis of removing speckle noise and improve the visual quality ofimage greatly.(3) According to the characteristics of medical image which has low contrast, amedical image enhancement method based on wavelet transform is proposed. Theexperimental results show that proposed method can enhance the outstanding the edgeinformation and the point position of medical image and help doctor improve thediagnostic accuracy in a great extent.(4) Using Microsoft Visual Studio2005to complete the design to build a medicalimage enhancement system. The system realized through the friendlyhuman-computer community has basic functions of the general image processing andthe specific denoising enhancement method, which is more convenient for medicalworkers to use and more effective for doctor to provide reliable basis for thediagnosis.The research content of this paper has laid a solid theoretical and technical basisfor the application research of medical image enhancement system.