Double Density Wavelet with Fast Bilateral Filter based Image Denoising for WMSN

Removal of Gaussian noise from the sensor imageduring acquisition is such a difficult task in the field of Wireless Multimedia Sensor Network (WMSN). There are several image denoising algorithms proposed so far in the field of WMSN to reduce the impact of noise over images. Out of various denoising algorithms, wavelets have shown superior performance as image denoising technique. However, the properties of wavelets may affect the denoised output significantly for different set of images. In order to avoid this, an attempt has been made in this paper to reduce the Gaussian noise during image acquisition by utilizing the double density dual tree wavelet transform. Further, the quality of the image can be enhanced by appending the Fast Bilateral Filter (FBF) with the double density wavelets. To understand the behavior of the double density wavelet based image denoising technique, it is simulated and compared with the existing dual tree complex wavelet transform based denoising technique for different noise levels by using MATLAB simulation