Most of the current speckle reduction system uses various filters .There are various filters for reducing the speckle noise reduction. But due to some drawbacks these traditional filters cannot remove speckle noise efficiently. So a hybrid technique speckle noise reduction using anisotropic filter based on wavelets is used. In this paper the necessary idea of an uncorrupted image from the noisy image is identified as “denoising”. Choosing the most excellent way plays a very important role for getting the desired image. So in this thesis report a study is made on “Speckle Noise reduction using anisotropic filter based on wavelets”. There are various existing techniques to remove the speckle noise reduction but due to some drawbacks these techniques cannot remove speckle noise efficiently. The adaptive filters that are Kuan filter, Lee filter, and Frost filter are not able to remove a full removal of speckle without losing any edges because they relies on local statistical data and this statistical data depends upon window size and shape. As these existing filters are very much sensitive to the window shape and window size. If the window shape is very much larger than over smoothing will occurs. As the size of window is smaller than the smoothing ability of the window will reduce. So to overcome these limitations, a new hybrid technique that combines wavelet based denoising and anisotropic diffusion filter is proposed. Wavelet is dependent on both frequency and time domain. It is frame based approach. It provides better resolution and it does not depend upon the window size. In addition the anisotropic filter is based on partial differential equation approach.