Analysis of Speckling Noises on US Kidney Images using Transform R.Vinoth 1 , Dr.K.Bommannaraja 2 1 Assistant Professor, 2 Principal, 1 Department of ECE, Muthayammal College of Engg, Rasipuram. 2 KPR Institute of Engg and Technology, Coimbatore 1 rvinothrathinam@gmail.com , 2 dr.k.bommannaraja@gmail.com Abstract Speckle is a multiplicative noise in an ultrasound image. The presence of speckle degrades the image quality. And it is difficult to diagnosing kidney images. The reduction of speckle is done with the novel speckle reduction method in the curvelet domain with coefficient modelling and diffusion filtering of coefficients. An undecimated Atrous based curvelet transform is done. A shrinkage function is estimated with the curvelet transformed coefficients using Maximum A posteriori Probability (MAP) technique. The part of curvelet coefficients are diffusion filtered using Perona Malik Anisotropic Diffusuion filter, and the remaining part of curvelet coefficients are modelled using the shrinkage function. The proposed algrorithm has been tested with the real time ultrasound kidney images. The performance of the proposed method is evaluated by using the quantitative measures such as Peak signal to noise ratio (PSNR), structural similarity index measure (SSIM) and coefficient of correlation (CoC). Index terms: Despeckling, Curvelet transform, diffusion filter, coefficient modelling, MAP estimation I.INTRODUCTION Digital image plays a vital role in our routine life, like computer resonance image, satellite and in research field. The image sensors collect the data sets which are corrupted by noise and it is caused by imperfect design of instrument. A digital image is normally encoded with a colour values or gray level values. 2D represents the gray level value image. In case of three dimension it is a video matrix. There are two limitations on accuracy of image is categorized as noise and blur. It degrades the image quality. Thus denoising is the necessary step for image analysis. There are effective techniques used to prevent the noise from the digital image. The image denoising is a bottleneck problem for the researchers because removal of noise causes the image bluring. This paper presents the methodologly for noise reduction and also evaluate the proposedbetter results that is reliable and appropriate estimate of the original image given its noisy version. There are several factors are used to model the noise, the factors are image capturing instrument, transmission media and quantisation of the image. Depending on the noise sources various algorithms used. In ultrasound images, the speckle noise is occur. For detecting low contrast lesion speckle is the primary limitation in ultrasound imaging [1]. Thus it considered as a noise source which should be reduced where asrician noise [2] is observed in MRI images. A. Ultrasound Image Medical ultrasonography uses high frequency broad band sound waves in the megahertz (MH) range that are reflected by tissue to varying degrees to produce images. The image is upto 3D. This is commonly associated with imaging the human kidney. Uses of ultrasound are much broader. Other important uses include imaging the abdominal organs, heart, breast, muscles, tendons, arteries and veins. While it may provide less anatomical detail than techniques such as CT or MRI, it has several advantages which make it ideal in numerous situations, in particular that it studies the function of moving structures in real-time, and it emits no ionizing radiation, and contains speckle noise. Ultrasound is also used as a popular research tool for capturing raw data. That can be made available through an ultrasound research interface, for the purpose of tissue characterization and implementation of new image processing techniques. The concepts of ultrasound is differ from other medical imaging modalities in the fact that it is operated by the transmission and receipt of sound waves. The high frequency sound waves are sent into the tissue and depending on the composition of the different tissues and the signal will be attenuated and returned at separate intervals. A path of reflected sound waves in a multi-layered structure can be defined by an input impedance that is ultrasound International Journal of Applied Engineering Research ISSN 0973-4562 Volume 10, Number 9 (2015) © Research India Publications ::: http://www.ripublication.com 8699