In medical image processing image denoising has become a very essential exercise all through the diagnose. Medical images are often deteriorated by noise due to a serious sources of interferences and other phenomenon that affect the measurement process in an imaging and acquisition system. Speckle noise is a random mottling of the image with bright and dark spots, which obscures fine details an...

In this paper, an underwater ambient noise (UWAN) removing framework based on generative adversarial network (GAN) to recover underlying ship-engine data is proposed. Unlike previously reported GAN-based denoising techniques, the proposed ambient-noise GAN (UWAR-GAN) modelled using both, log magnitudes as well phase information with significant time-frequency resolution. The as-developed integr...

In this paper, we propose a new method to reconstruct signal corrupted by noise where both and are sparse but in different domains. The main contribution of our algorithm is its low complexity; it has much lower run-time than most other algorithms. reconstruction quality objectively (in terms PSNR SSIM) subjectively better or comparable state-of-the-art We provide cost function for problem, pre...

The analysis in this paper represents the first attempt to examine whether forecasting performance of one GARCH models can be improved after removing noise from stock market returns. Doing on eight developed markets helps providing reliable results that generalized more markets. This then examines ability forecast return volatility under a range statistical forecasts. We specifically employ mul...

Recently many mathematical models for image processing have been widely applied in computer visualization. The nonlinear diffusion PDE has been broadly applied in image processing. In this paper we propose a convection-diffusion filter by adding a convection term in the modified diffusion equation as a physical interpretation for removing the noise. We study the dynamics of such equations by th...

In this paper, we propose an efficient algorithm for removing salt and pepper noise in images. The process of denoising is implemented two stages: detection followed by removal. For detection, extreme intensity values image are used to detect possible “noise pixels”. removal, the switching mechanism only selects pixels” processing avoid altering any fine details, identified noise-free pixels ac...