There are many unavoidable noise interferences in image acquisition and transmission. To make it better for subsequent processing, the noise in the image should be removed in advance. There are many kinds of image noises, mainly including salt and pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoising alg...

the edges of an image define the image boundary. when the image is noisy, it does not become easy to identify the edges. therefore, a method requests to be developed that can identify edges clearly in a noisy image. many methods have been proposed earlier using filters, transforms and wavelets with ant colony optimization (aco) that detect edges. we here used aco for edge detection of noisy ima...

Among the various approaches for producing point distributions with blue noise spectrum, we argue an optimization framework using Gaussian kernels. We show that a wise selection of parameters, this approach attains unprecedented quality, provably surpassing current state art attained by optimal transport (BNOT) approach. Further, our algorithm scales smoothly and feasibly to high dimensions whi...

MRI is one of the most powerful techniques to study the internal structure of the body. MRI image quality is affected by various noises. Noises in MRI are usually thermal and mainly due to the motion of charged particles in the coil. Noise in MRI images also cause a limitation in the study of visual images as well as computer analysis of the images. In this paper, first, it is proved that proba...

the presence of noise in geophysical measurements has undesirable effects on the seismic data. one of the important problems in seismic data processing is attenuation of the noise to the desired form and keeping the original signal. contamination of seismic data with noise prevents obtaining a proper image of geological structures and seismic data interpretation. in some of the receivers the no...

Background: Nowadays, image de-noising plays a very important role in medical analysis applications and pre-processing step. Many filters were designed for image processing, assuming a specific noise distribution, so the images which are acquired by different medical imaging modalities must be out of the noise. Objectives: This study has focused on the sequence filters which are selected ...

conclusions in the case of existence gaussian noise, the results confirm that denoising is not effective on the measurement of t2* value. in the case of image distortion by rician noise, a predictor model is proposed to estimate the original t2* value. the predictor model is used to estimate the t2* value of new patients. the predicted t2* values were in good agreement with the corresponding or...

A detector for the case of a radar target with known Doppler and unknown complex amplitude in complex Gaussian noise with unknown parameters has been derived. The detector assumes that the noise is an Auto-Regressive (AR) process with Gaussian autocorrelation function which is a suitable model for ground clutter in most scenarios involving airborne radars. The detector estimates the unknown...

conclusion various filters are needed to improve the image quality. in this study, seven different filters were implemented and investigated on both noisy and noise-free images. background developmental dysplasia of the hip (ddh) can be detected with ultrasonography (usg) images. however, the accuracy of this method is dependent on the skill of the radiologist. radiologists measure the hip join...