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Research on Simulations and Modified Algorithms of Median Filter

Author: CaoZhenMing
Tutor: YuanPing
School: Northeastern University
Course: Communication and Information System
Keywords: image denoising median filter noise detection adaptive filter
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 135
Quote: 1
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Abstract


During the process of formation and transmission, images are often disturbed by different types of noises, which degrade image quality. Various linear or nonlinear filtering methods are employed to reduce or remove noises. Different from the linear filter, the nonlinear filter can not only remove noise effectively but also keep the details of the digital images, so images can be clearer and more vivid. As an effective processing technology, the non-linear filter is widely used in the digital image processing. Median filters are representative. The typical median filter can remove the impulse noise, but it also corrupts some very important details of the images. There are many improved median filters firstly suggested to overcome the problems. Based on the situation of median filter, this paper carried out the subject research.This paper mainly lucubrated the filtering of impulse noise in images, and two modified algorithms are proposed. This paper includes mainly two parts as follows. In the first part, the standard median filter and its improved algorithms are analyzed and studied, and the paper gives an adaptive median filter algorithm based on detection of impulse noise. The experimental results show that the proposed method can not only remove impulse effectively but also preserve image’s details well. In the second part, based on the RAMF algorithm, the measure of MGD (Minimum Gray-value Difference) is introduced to modify RAMF, and a new algorithm is proposed. The results of comparison experiments with RAMF and NASMF demonstrate that the proposed method can remove noise efficiently while retaining image details. The proposed algorithm is better than the others especially to images with high noise density.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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