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A new wavelet hard threshold to process image with strong Gaussian Noise

机译:一种新的小波硬阈值,以处理具有强高斯噪声的图像

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Wavelet transform method has been widely used in image filtering, the wavelet threshold de-noising method can treat Gaussian noise with randomness well. This paper proposes that after the wavelet transform the high frequency coefficients need a more accurate processing, And the classical hard threshold method has been improved by introducing the measure of medium truth scale. The new method can effectively handle strong Gaussian noise with larger variance through theoretical analysis and experimental simulation, and get a fine recovery image. It also provides a new approach for wavelet de-noising.
机译:小波变换方法已广泛用于图像滤波,小波阈值脱光方法可以用随机性处理高斯噪声。 本文提出,在小波变换之后,高频系数需要更准确的处理,并且通过引入中等真理规模的测量来提高经典硬阈值方法。 新方法可以通过理论分析和实验模拟有效地处理强大的高斯噪声,方差较大,并获得精细恢复图像。 它还提供了一种新的小波去噪方法。

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