Performance Analysis Of Medical Image Enhancement Based On Wavelet Transform

The wavelet transform is improvement and extension of Fourier transformcogitation. Image enhancement is very important for Image processing. Wavelettransform as a new and effective tools of image processing, has been a great concern.Some noise exist in medical image by itself, and then image quality is descendmoreover low contrast, details are not clear, as long as it be enhanced then to meetthe needs of the clinical diagnosis. The article mainly discussed the apply on themedical image enhancement with biorthogonal wavelet transform and dyadic wavelettransform. Since the biorthogonal wavelet transform is of down-sampling type andthe demerit of being not shift-invariant, casue some poor accuracy of the imageprocessing. However, the dyadic wavelet transform is shift-invariant and don’tsample, so it has the best property on the accuracy of the image processing. So, westudy on enhancement of medical images with the improvement enhancementfunction based on the dyadic wavelet transform theory. First, analyze the soft andhard threshold function, give an account of the advantages and disadvantages withlinear enhancement function and nonlinear enhancement function. Through adjustingthe threshold and form of the free parameters, we can find threshold value andenhancement function for medical image enhancement. From experiments can knowit has the different effection for different types of image process with an enhancedfunction and the threshold value. In this article, based on the single thresholdenhancement function, found dual threshold enhancement function, enhancementvalue and free parameters for medical image enhancement. Owing to antisymmetricbiorthogonal wavelet also has the differential operator function that translationalinvariance as dyadic wavelet. Start from the dyadic wavelet transform, discussing theeffect of medical image enhancement with the dyadic wavelet transform, firstintroduce the basic theory of the wavelet transform. Compare the dyadic wavelet andbiorthogonal wavelet. And discussing the linear enhancement function, nonlinearenhancement function. Use difference enhancement function experiment toLow-frequency and high-frequency part which decomposed by different wavelet, andcompare, observed enhanced performance, at the same time, do some theoreticalresearch.Then, in order to verify the effectiveness of the enhancement function andthreshold value which used for medical image processing, do some comparativeexperiments. Enhance a medical image with use the single threshold enhancement function for low-frequency and use the dual threshold enhancement function forhigh-frequency, the index of enhance evolution is better than to deal with the singlethreshold enhancement function, can be obtained a medical image which has a bettervisual effect, higher contrast, more prominent details. This will help assist doctorscanget a diagnosis and differential which is very clear and accurate. It is in favor ofassisting doctors in diagnosising, and offers reference for development of radiology.