IMAGE SMOOTHING MENGGUNAKAN MEAN FILTERING, MEDIAN FILTERING, MODUS FILTERING DAN GAUSSIAN FILTERING

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...

Weighted Repeated Median Smoothing and Filtering

Mean – Median Filtering For Impulsive Noise Removal

Abstrak –The objective of this paper is a new MeanMedian filtering for denoising extremely corrupted images by impulsive noise. Whenever an image is converted from one form to another, some of degradation occurs at the output. Improvement in the quality of these degraded images can be achieved by the application of Restoration and /or Enhancement techniques. Noise removing is one of the categor...

Bayesian Filtering and Smoothing

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications, and medicine. This compact, informal introduction for graduate students an...

Does Median Filtering Truly Preserve Edges Better than Linear Filtering ?

Image processing researchers commonly assert that “median filtering is better than linear filtering for removing noise in the presence of edges.” Using a straightforward large-n decision-theory framework, this folk-theorem is seen to be false in general. We show that median filtering and linear filtering have similar asymptotic worst-case meansquared error (MSE) when the signal-to-noise ratio (...