Using bivariate Gaussian distribution for image denoising in the 2-D complex wavelet domain

Within this framework we describe a novel technique for removing noise from digital noisy images, based on the modeling of wavelet coefficient with bivariate normal distribution and statistical calculation. A method for image denoising is presented in this paper to maximize a posterior density function (MAP) estimator using a bivariate normal random variable. We use our denoising algorithm in 2-D complex wavelet domain comparing with soft and hard thresholding method of stationary wavelet analysis tool (2-D SWT). Despite the simplicity of our method in its implementation, our denoising results achieves better performance than the other mentioned methods both visually and in terms of peak signal-to-noise ratio (PSNR).