汪祖辉,孙刘杰,邵雪.一种改进的三维块匹配图像去噪算法[J].包装工程,2016,37(21):198-203.
WANG Zu-hui,SUN Liu-jie,SHAO Xue.An Improved Block Matching 3D Filtering Image Denoising Algorithm[J].Packaging Engineering,2016,37(21):198-203. |
| 一种改进的三维块匹配图像去噪算法 |
| An Improved Block Matching 3D Filtering Image Denoising Algorithm |
| 投稿时间：2016-04-22 修订日期：2016-11-10 |
| DOI： |
| 中文关键词: 图像去噪 块匹配 三维变换 中值滤波 |
| 英文关键词: image denoising block-matching 3D transform median filtering |
| 基金项目:上海市教委科研创新重点资助项目（13ZZ111） |
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| 中文摘要: |
| 目的 为了有效消除噪声图像中的椒盐噪声、高斯噪声甚至混合噪声，改进三维块匹配算法，提出一种新的图像去噪算法。方法 首先，该算法将含噪声图像用图像块之间的相似性构建三维矩阵。然后，在图像块之间进行硬阈值滤波降低噪声，对图像块集合加权平均重建得到初步估计去噪图像。最后，对初步估计结果图像进行块匹配，在图像块内和图像块之间进行维纳滤波和加权中值滤波，得到最终去噪图像。结果 仿真结果表明，该算法对图像采集的常见噪声均表现出理想的去噪效果，PSNR值均大于31 dB。对比维纳滤波、中值滤波、硬阈值小波滤波，文中算法对高斯噪声、椒盐噪声和混合噪声的去噪结果PSNR值为31.5334～36.6466 dB，均高于其他算法，最高差值达到12.08 dB。结论 结合中值滤波和三维块匹配算法的图像去噪算法，能够较好去除噪声图像的多种类型噪声，是一种较为优秀的去噪算法。 |
| 英文摘要: |
| In order to effectively eliminate noise image with impulse noise, Gaussian noise and even mixed noise, the work improves the 3D block-matching algorithm and puts forward a new image denoising algorithm. Firstly, the 3D matrix was constructed with the similarity between image block of noise image. Then, the noise was attenuated by hard-thresholding between the image blocks, and the initially estimated denoised images were obtained through the weighted average reconstruction of image blocks. Finally, block-matching was performed on the initially estimated denoised images, and Wiener filtering and weighted median filtering were conducted in and among image blocks, finally denoised images were obtained. Simulation results showed that the proposed algorithm had ideal denoising effect on common noise of image acquisition, and the PSNR value was more than 31 dB. Compared with Wiener filtering, median filtering and hard threshold wavelet filtering, PSNR results of Gaussian noise, impulse noise and mixed noise with this algorithm were 31.5334～36.6466 dB, higher than other algorithms. The highest difference value reached 12.08 dB. In conclusion, image denoising method combined with median filter and 3D block-matching algorithm can better reduce a variety of noises and is an excellent denoising algorithm. |
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