An Effective Denoising Method for Images Contaminated with Mixed Noise Based on Adaptive Median Filtering and Wavelet Threshold Denoising
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초록
Images are unavoidably contaminated with different types of noise during the processes of image acquisitionand transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) andGaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. Ingeneral, different types of denoising methods are designed for different types of noise; for example, themedian filter displays good performance in removing impulse noise, and the wavelet denoising algorithmdisplays good performance in removing Gaussian noise. However, images are affected by more than one typeof noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoisingmethod that combines adaptive median filtering (AMF) based on impulse noise detection with the waveletthreshold denoising method based on a Gaussian mixture model (GMM). The simulation results show thatthe proposed method achieves much better denoising performance than the median filter or the waveletdenoising method for images contaminated with mixed noise.
Abstract
Images are unavoidably contaminated with different types of noise during the processes of image acquisitionand transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) andGaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. Ingeneral, different types of denoising methods are designed for different types of noise; for example, themedian filter displays good performance in removing impulse noise, and the wavelet denoising algorithmdisplays good performance in removing Gaussian noise. However, images are affected by more than one typeof noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoisingmethod that combines adaptive median filtering (AMF) based on impulse noise detection with the waveletthreshold denoising method based on a Gaussian mixture model (GMM). The simulation results show thatthe proposed method achieves much better denoising performance than the median filter or the waveletdenoising method for images contaminated with mixed noise.
참고문헌 (18)
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