White noise stimuli are frequently used to study the visual processing of broadband images in the laboratory. A common goal is to describe how responses are derived from Fourier components in the image. We investigated this issue by recording the ocular-following responses (OFRs) to white noise stimuli in human subjects. For a given speed we compared OFRs to unfiltered white noise with those to...

This paper presents an outline for removing noise in digital images. We see that the real time images are get more corrupted while acquisition, processing and transmission. As we deal 98% of our daily work on real time application data. So to suppress noise and elimination of noise from real time images is a research area for the developers, that how to predict noise and to remove that one nois...

There are two main approaches for pore pressure estimation: geological using basin modeling and geophysical using seismic velocity. In this paper, seismic velocity was used for pore pressure estimation. The impact of the input data quality in terms of signal-to-noise ratio (SNR) and frequency bandwidth on the accuracy of seismic velocity analysis and, ultimately, the reliability of pore pressur...

In many practical classification problems, mislabeled data instances (i.e., class noise) exist in the acquired (training) data and often have a detrimental effect on the classification performance. Identifying such noisy instances and removing them from training data can significantly improve the trained classifiers. One such effective noise detector is the so-called ensemble filter, which pred...

Images plays vital role in our daily life. Noise is one of the important limitation in digital image processing. Noise is basically the type of unwanted disturbance in the image. A lot study is made so outlying to diminish or confiscate noise from digital images. Most of the filter fails when the noise density is very high. This paper proposes improved modified decision based median filter whic...

We present a Field Programmable Logic Devices (FPLDs) based implementation of a scalable filter architecture capable of detecting and removing impulsive noise in image sequences. The adaptive filter architecture is built using switching spatiotemporal filtering scheme and robust Lower-Upper-Middle (LUM) based noise detector. It uses highly optimized bit-serial pipelined implementation in Altera...

Removing noise from the Medical image is still a challenging problem for researchers. Noise added is not easy to remove from the images. There have been several published algorithms and each approach has its assumptions, advantages, and limitations. This paper summarizes the major techniques to denoise the medical images and finds the one is better for image denoising. We can conclude that the ...

Enhancement is one of the challenging factors in image processing. The objective of enhancement is to improve the structural appearance of an image without any degradation in the input image. The enhancement techniques make the identification of key features easier by removing noise and other artifacts in an image. This paper analyzes the performance of various enhancement techniques based on n...

A novel post-processing approach for removing Monte Carlo noises in synthetic images is presented in this paper. This paper first presents our findings on the statistical characteristics of the Monte Carlo noise, and then proposes a Bayesian method to remove this noise. The aim of this approach is to efficiently produce high quality synthetic images using Monte Carlo based rendering at low samp...