Performance comparison of contourlet and wavelet transform in denoising of ultrasound image

Pictures are simple way of representing information. At the time of applying operations like segmentation, feature extraction, feature analysis image should be noise free. The purpose of image de-noising process is to eliminate the without affecting actual quality of image. Introduction of noise is due to disgraceful securing, transmission and gathering and capacity and recovery forms. As noise gets introduced in image, there is degradation in visual quality of image. There are many types of noises present into image such as Speckle noise, Additive noise. Impulse noise is a most ordinarily show in every single medicinal picture including ultrasound pictures. To extract useful information from image it is to be restored in the original form so, for restoration of image transformations are to use. DWT (Discrete wavelet transform) and contourlet transform are the new methods for image restoration. In this paper comparative analysis of various de-noising techniques based on contourlet and wavelet transform is presented. Examination of Haar DWT and Symlet DWT with wiener and median filtering systems and contourlet change is finished. Result analysis is done in terms of Peak Signal to Noise Ratio, Mean squared Error and computational time.