Molecular Filters for Noise Reduction

Histogram Filters for Noise Reduction

A class of filters based on histograms are presented. The signal probability density function is estimated and filtering is performed in the pdf domain. Such filters can be designed to preserve signal features such as sharp edges while suppressing stochastic variations. One particular histogram filter scheme is evaluated and compared to a median filter and a normal gaussian blurring filter.

Performance Evaluation of Noise Reduction Filters

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...

Optimal Time-Domain Noise Reduction Filters - ReadingSample

Evaluation of Infrasonic Noise Reduction Filters

It is generally accepted that the study of acoustic signals in the atmosphere requires suppression of noise due to atmospheric turbulence. Most acoustic signals of interest arrive with longer spatial wavelengths than the noise that originates near the receiver. As a result, integration of acoustic energy across an area will attenuate spatially de-correlated noise and increase the signal-to-nois...

Circular Mean Filtering For Textures Noise Reduction

In this paper, a special preprocessing operations (filter) is proposed to decrease the effects of noise of textures. This filter using average of circular neighbor points (Cmean) to reduce noise effect. Comparing this filter with other average filters such as square mean filter and square median filter indicates that it provides more noise reduction and increases the classification accuracy...