针对混合噪声特点不一致，抑制难度较大的问题，为提升噪声抑制效果，提高图像清晰度，提出一种基于提升小波的数字图像混合噪声抑制算法。通过概率神经网络将数字图像噪声划分为脉冲噪声和高斯噪声，采用中值滤波方法去除数字图像中的脉冲噪声，运用提升小波方法去除数字图像中的高斯噪声，实现混合噪声的抑制。实验结果表明，所提算法获得的图像清晰度和信噪比更高，且去噪后数字图像的ENOB(Effective Number Of Bits)值明显提升，说明该算法的混合噪声抑制效果更佳。
Mixed Noise Suppression Algorithm of Digital Image Based on Lifting Wavelet
Unlike single noise,mixed noise has inconsistent characteristics and is difficult to suppress.In order to improve the noise suppression effect and image clarity,a digital image mixed noise suppression algorithm based on lifting wavelet is proposed.By using probabilistic neural networks,digital image noise is divided into pulse noise and Gaussian noise.The median filtering method is used to remove pulse noise from the digital image,and the lifting wavelet method is used to remove Gaussian noise from the digital image,achieving mixed noise suppression.The experimental results show that the proposed algorithm achieves higher image clarity and signal-to-noise ratio,and significantly improves the ENOB(Effective Number Of Bits)value of the digital image after denoising,indicating that the hybrid noise suppression effect of the algorithm is better.
digital imagemedian filteringlifting waveletimpulse noisegaussian noise
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