Hou Yingkun, Shen Dinggang
School of Information Science and Technology, Taishan University, Taian 271000, China.
Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
EURASIP J Image Video Process. 2018;2018. doi: 10.1186/s13640-018-0301-y. Epub 2018 Jul 20.
BM3D is a state-of-the-art image denoising method. Its denoised results in the regions with strong edges can often be better than in the regions with smooth or weak edges, due to more accurate block-matching for the strong-edge regions. So using adaptive block sizes on different image regions may result in better image denoising. Based on these observations, in this paper, we first partition each image into regions belonging to one of the three morphological components, i.e., contour, texture, and smooth components, according to the regional energy of alternating current (AC) coefficients of discrete cosine transform (DCT). Then, we can adaptively determine the block size for each morphological component. Specifically, we use the smallest block size for the contour components, the medium block size for the texture components, and the largest block size for the smooth components. To better preserve image details, we also use a multi-stage strategy to implement image denoising, where every stage is similar to the BM3D method, except using adaptive sizes and different transform dimensions. Experimental results show that our proposed algorithm can achieve higher PSNR and MSSIM values than the BM3D method, and also better visual quality of denoised images than by the BM3D method and some other existing state-of-the-art methods.
BM3D是一种先进的图像去噪方法。由于对强边缘区域进行了更精确的块匹配，其在强边缘区域的去噪结果通常比在平滑或弱边缘区域更好。因此，在不同图像区域使用自适应块大小可能会带来更好的图像去噪效果。基于这些观察结果，在本文中，我们首先根据离散余弦变换（DCT）的交流（AC）系数的区域能量，将每个图像划分为属于三种形态成分之一的区域，即轮廓、纹理和平滑成分。然后，我们可以为每个形态成分自适应地确定块大小。具体来说，我们对轮廓成分使用最小的块大小，对纹理成分使用中等块大小，对平滑成分使用最大的块大小。为了更好地保留图像细节，我们还使用多阶段策略来实现图像去噪，其中每个阶段类似于BM3D方法，但使用自适应大小和不同的变换维度。实验结果表明，我们提出的算法比BM3D方法能获得更高的峰值信噪比（PSNR）和多尺度结构相似性（MSSIM）值，并且去噪图像的视觉质量也比BM3D方法和其他一些现有的先进方法更好。
