JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
An Effective Denoising Method for Images Contaminated with Mixed Noise Based on Adaptive Median Filtering and Wavelet Threshold Denoising |
| 영문제목(English Title) |
An Effective Denoising Method for Images Contaminated with Mixed Noise Based on Adaptive Median Filtering and Wavelet Threshold Denoising |
| 저자(Author) |
Sung-Hoon Lee
Jong-hyuk Roh
SooHyung Kim
Seung-Hun Jin
Lin Lin
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| 원문수록처(Citation) |
VOL 14 NO. 02 PP. 0539 ~ 0551 (2018. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.
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| 키워드(Keyword) |
Feature Subset
Keystroke Dynamics
Smartphone Sensor
Adaptive Median Filter (AMF)
Gaussian Mixture Model (GMM)
Image Denoising
Mixed Noise
Wavelet Threshold Denoising
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| 파일첨부 |
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