【摘要】 为了提高图像的去噪效果,根据复方向滤波器组和BlockShrink的特点,提出了一种新的图像去噪算法。首先对图像进行复方向滤波器组分解得到系数,然后根据系数间的相关性采用块阈值方法选择最佳的块大小和阈值,使每个子带的无偏风险估计值最小。该算法是完全基于数据驱动的方法,具有算法简单、易于实现、视觉效果好等特点。实验表明,该算法比基于DWT变换的BlockShrink算法其信噪比提高了0.6%,在视觉效果方面边缘和轮廓信息更清晰。更多还原

【Abstract】 A new image denoising algorithm based on the complex direction of filter bands and BlockShrink is proposed.The image is decomposed based on the complex direction of filter bands to obtain the coefficients.Then,according to the coefficient correlation,the block threshold method is used to select the best block size and the threshold.In this way,the unbiased risk estimation of each sub-band is minimized.The algorithm is entirely data-driven easy to implement and with good visual effects.Experiments show that the proposed algorithm increase the PSNR by 0.6 percent compared with the algorithm based on DWT-BlockShrink transform,and the edge and countour information are more clearly.更多还原