A New Bivariate Shrinkage Denoising of Remotely Sensed Images with Discrete Shearlet Transform (DST)
R. M. Gomathi, S Selvakumaran · 2018
In the process of remotely sensed image acquisition and transmission, the results are easily affected by noise interference, resulting in lower image quality. However, for further image analysis and also in many applications, high-quality images are required. Therefore, denoising of remotely sensed images is of great importance. In this paper, a new bivariate shrinkage function with Discrete Shearlet Transform (DST) transform is proposed for remotely sensed image denoising which adaptively smoothes the images as well as retains the subtle details. The iterative Successive Substitution Method (SSM) is used for solving the Non-Linear Equations to get desired results. The performance of the proposed method is measured by using the Peak Signal to Noise Ratio (PSNR). The experimental results show that the proposed method gives higher PSNR when compared with the traditional Discrete Wavelet Transform (DWT) methods.