Present investigation reveals the quantum of work carried in the filtering methods for image denoising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De-noising of natural images is appears to be very...

In magnetic resonance imaging (MRI) images, noise is a common issue and it is locally signal dependent. Theoretical expectation of noise measured in unfiltered images is found to be normally distributed, spatially invariant and white. Therefore, the noise has to be removed before processing stage. In this work, there are three different filtering algorithms which are median filter (MF), adaptiv...

Image restoration is an essential issue in high level image processing which deals with recovering of an original and sharp image using a degradation and restoration model. Through image acquisition process degradation occurs. Image restoration is used to estimate the unique image from the degraded data. The degradations include half toning, dithering and security watermarks. An iterative image...

This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis ...

CT image De-noising is an important research topic both in image processing and biomedical engineering. Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. The curvelet transform as a multiscale transform has directional parameters occurs at all scale...

In this paper, an approach of principal component analysis (PCA) with local pixel grouping (LPG) is used to de-noising the noisy historical document image. This technique ensures the preservation of historic document image local structure. This is due to block matching based LPG which carries out classification to allow only the sample blocks with similar contents used in the calculation for PC...

In ultrasonic testing of welding flaws, the reliability and quality of tests are considerably affected by noise and spurious signals. Thus, signal de-noising and increasing of the signal-noise ratio (SNR) are a key to successful application of ultrasonic NDT and NDE. At present, there are many methods for signal de-noising, such as median filtering, non-linear filtering, adaptive filtering, cor...

Medical images have noise, such as salt and pepper, speckle, gaussian noise. So, getting the accuracy of magnetic resonance is challenging always. The brain essential for clinical diagnosis process. nonlinear method median morphological filters used enhancement, contrast adjustment, histogram equalization medical speech processing, to preserve them from noise edge features. Because its edge-pre...

The de-noising of an image corrupted by Gaussian noise is a classical problem in signal or image processing. An image is often corrupted by noise during its acquisition and transmission. Image de-noising is used to reduce the noise while retaining the important features in the image. Always there exists a tradeoff between the removed noise and the blurring in the image. The use of wavelet trans...