论文标题
图像斑点噪声通过基于块匹配和3D滤波的多层融合增强方法降解
Image Speckle Noise Denoising by a Multi-Layer Fusion Enhancement Method based on Block Matching and 3D Filtering
论文作者
论文摘要
为了改善基于nonsabsampled contourlet变换（NSCT）的图像频率域多层融合增强方法（MLFE-BM3D）的块匹配3D滤波（BM3D）方法的斑点噪声降解。该方法设计了NSCT硬阈值降级增强以进行图像进行预处理，然后使用NSCT结构域中的融合增强来融合NSCT硬阈值前后的图像的预估计结果，最后，BM3D Denoising使用融合图像进行了融合图像来获得最终的DeNoe deNoE效果。关于自然图像和医疗超声图像的实验表明，MLFE-BM3D方法比BM3D方法获得更好的视觉效果，DeNoed图像的峰信号与噪声比（PSNR）增加了0.5dB。 MLFE-BM3D方法可以改善纹理区域中斑点噪声的脱氧作用，并且仍然在图像的光滑区域保持良好的降解作用。
In order to improve speckle noise denoising of block matching 3d filtering (BM3D) method, an image frequency-domain multi-layer fusion enhancement method (MLFE-BM3D) based on nonsubsampled contourlet transform (NSCT) has been proposed. The method designs a NSCT hard threshold denoising enhancement to preprocess the image, then uses fusion enhancement in NSCT domain to fuse the preliminary estimation results of images before and after the NSCT hard threshold denoising, finally, BM3D denoising is carried out with the fused image to obtain the final denoising result. Experiments on natural images and medical ultrasound images show that MLFE-BM3D method can achieve better visual effects than BM3D method, the peak signal to noise ratio (PSNR) of the denoised image is increased by 0.5dB. The MLFE-BM3D method can improve the denoising effect of speckle noise in the texture region, and still maintain a good denoising effect in the smooth region of the image.
