关键词: 边界判定噪声检测, 贝叶斯最小平方-高斯尺度混合模型, 混合噪声

Abstract: Digital images are often contaminated by noise during image acquisition and transmission.Sometimes，noise is a mixed one of Gaussian noise and impulse noise.Unfortunately，existing denoising algorithms are often designed for removing single Gaussian noise or impulse noise.In this paper，an efficient method for removing Gaussian-Impulse mixed noise is proposed，which can be described as follows：Firstly，Boundary Discriminate Noise Detection（BDND） is applied to detect pixels corrupted by impulse noise，then the noisy image is filtered according to a decision map and an image corrupted by Gaussian noise is obtained；Secondly，Bayes Least Squares-Gaussian Scale Mixtures（BLS-GSM） is utilized to denoise the obtained image.Experimental results show that the proposed method can efficiently remove mixed noise.

Key words: Boundary Discriminate Noise Detection（BDND）, Bayes Least Squares-Gaussian Scale Mixtures（BLS-GSM）, mixed noise