A scheme combining multichannel crosstalk resistant adaptive noise cancellation (MCRANC) algorithm and improved spectrum subtraction (ISS) algorithm is presented to enhance noise carrying speech signals. The scheme would permit locating the microphones in close proximity by virtue of using MCRANC which has the capability of removing the crosstalk effect. MCRANC would also permit canceling out n...

This work deals with noise removal by the use of an edge preserving method called Perona–Malik diffusion or anisotropic diffusion[2][3]. This technique is used for image restoration without removing significant parts of the image content, typically edges or other details. In this scheme anisotropic diffusion is performed on DWT domain[1][7] which is more stationary than noisy image domain. In D...

Due to its high capability in acquiring spectral and spatial information, hyperspectral imaging technology has gained significant attention remote sensing. However, practice, it is impossible avoid noise hyper images due camera artifacts the external environment during acquisition transmission process. The presence of these hinders detection subtle differences between different materials image....

Intermittent fluid pulses in the Earth’s crust can explain a variety of geological phenomena, for instance the occurrence of hydraulic breccia. Fluid transport in the crust is usually modeled as continuous Darcian flow, ignoring that sufficient fluid overpressure can cause hydraulic fractures as fluid pathways with very dynamic behavior. Resulting hydraulic fracture networks are largely self-or...

In this paper, noise reduction scheme for images corrupted by various types of noise is presented. The efficient schemes are used to reduce the various types of noises. Images are often degraded by noise. Noise can occur during image capture, transmission, etc. Noise removing is an important mission in image processing. Generally the quality of the image processing technique has been strongly i...

The method of removing the existing Impulse noise was to find threshold and apply median filter remove noise. In this paper, we try reference values in neural networks. order noise, used a non-local consider not only information region but also entire region. We then utilized Yolo's grid cell structure make stronger predictions considering various sizes different areas. Accordingly, qualitative...

Cross-correlation of 1 month of ambient seismic noise recorded at USArray stations in California yields hundreds of short-period surface-wave group-speed measurements on interstation paths. We used these measurements to construct tomographic images of the principal geological units of California, with low-speed anomalies corresponding to the main sedimentary basins and high-speed anomalies corr...

Incoherent noise attenuation remains a challenging problem in seismic data processing. While many tools are successful at removing noise, this often comes at the expense of some signal. We seek the ideal noise attenuator– one that is effective, practical, and above all safe. Multichannel Singular Spectrum Analysis (MSSA) is a step in this direction. MSSA exploits the spatial redundancy of data ...

As financial time series are inherently noisy and non-stationary, it is regarded as one of the most challenging applications of time series forecasting. Due to the advantages of generalization capability in obtaining a unique solution, support vector regression (SVR) has also been successfully applied in financial time series forecasting. In the modeling of financial time series using SVR, one ...

Image Filtering is a technique of removing unwanted Noise from image so that the image can be improved in terms of brightness and noise and contrast. Although there are various technique implemented for the Image Degradation and removing Noise level from image such as using Gaussian Blur. The Existing Gaussian Blur technique is an efficient technique which provides more Peak Signal to Noise Rat...