高斯噪声是闪光图像中的主要噪声,将在密度反演等后续处理中被放大,严重影响密度重建及客体边界提取结果,因此,消高斯噪声是闪光图像消噪研究的重点内容。针对闪光照相图像噪声及照相客体轴旋转对称的特点,研究了基于三维块匹配滤波(Blo...高斯噪声是闪光图像中的主要噪声,将在密度反演等后续处理中被放大,严重影响密度重建及客体边界提取结果,因此,消高斯噪声是闪光图像消噪研究的重点内容。针对闪光照相图像噪声及照相客体轴旋转对称的特点,研究了基于三维块匹配滤波(Block Matching and 3D Filtering,BM3D)的闪光照相图像消噪算法,针对闪光照相图像中难以获得更高质量相似块的缺陷,在不破坏噪声独立性的情况下,通过对含噪退化图像进行旋转与镜像操作,增加了提供相似块的图像来源。同时,通过引入图像块的灰度变换,降低了原有相似性要求中的灰度值要求,提高了形状相似的要求,增加了获得高质量相似块的能力。图像的消噪结果表明,由于相似块的质量得到保证,用于闪光图像消噪的改进BM3D方法取得了更好的消噪效果。展开更多
Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to ...Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.展开更多
针对低剂量CT图像质量退化问题,提出了一种基于投影域数据恢复的低剂量CT优质重建方法。新方法首先通过非线性Anscombe变换将满足Poisson分布的投影域数据转化Gaussian型分布,然后利用针对Anscombe变换的Gaussian型数据进行自适应Block-...针对低剂量CT图像质量退化问题,提出了一种基于投影域数据恢复的低剂量CT优质重建方法。新方法首先通过非线性Anscombe变换将满足Poisson分布的投影域数据转化Gaussian型分布,然后利用针对Anscombe变换的Gaussian型数据进行自适应Block-Matchingand 3D filtering(BM3D)滤波,最后通过对Anscombe逆变换数据执行传统的滤波反投影(Filtered Back Projec-tion,FBP)CT重建。由于Anscombe变换数据的方差已知,且所用BM3D滤波无需人工设置滤波参数,使得方法可实现自适应低剂量CT图像重建。仿真和临床低剂量CT数据的实验表明,方法具有良好的重建鲁棒性,其重建图像的噪声和伪影可同时得到有效抑制。展开更多
在处理由椒盐噪声污染的高对比度图像时,使用传统的三维块匹配算法(Block-Matching and 3D filtering,BM3D)去噪不能有效保留图像的边缘和纹理细节,在图像的边缘会出现边缘振铃效应。为了改善传统BM3D算法在处理椒盐噪声时的不足,提出...在处理由椒盐噪声污染的高对比度图像时,使用传统的三维块匹配算法(Block-Matching and 3D filtering,BM3D)去噪不能有效保留图像的边缘和纹理细节,在图像的边缘会出现边缘振铃效应。为了改善传统BM3D算法在处理椒盐噪声时的不足,提出了用边缘方向代替水平方向搜索相似块的BM3D改进去噪算法。实验结果表明,改进BM3D算法获得的相似块数量是传统BM3D算法的3倍,峰值信噪比(PSNR)也得到进一步提高,在去除椒盐噪声的同时也使图像边缘得到有效保留。展开更多
文摘高斯噪声是闪光图像中的主要噪声,将在密度反演等后续处理中被放大,严重影响密度重建及客体边界提取结果,因此,消高斯噪声是闪光图像消噪研究的重点内容。针对闪光照相图像噪声及照相客体轴旋转对称的特点,研究了基于三维块匹配滤波(Block Matching and 3D Filtering,BM3D)的闪光照相图像消噪算法,针对闪光照相图像中难以获得更高质量相似块的缺陷,在不破坏噪声独立性的情况下,通过对含噪退化图像进行旋转与镜像操作,增加了提供相似块的图像来源。同时,通过引入图像块的灰度变换,降低了原有相似性要求中的灰度值要求,提高了形状相似的要求,增加了获得高质量相似块的能力。图像的消噪结果表明,由于相似块的质量得到保证,用于闪光图像消噪的改进BM3D方法取得了更好的消噪效果。
基金supported by the National Natural Science Foundation of China(6157206361401308)+6 种基金the Fundamental Research Funds for the Central Universities(2016YJS039)the Natural Science Foundation of Hebei Province(F2016201142F2016201187)the Natural Social Foundation of Hebei Province(HB15TQ015)the Science Research Project of Hebei Province(QN2016085ZC2016040)the Natural Science Foundation of Hebei University(2014-303)
文摘Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.
文摘针对低剂量CT图像质量退化问题,提出了一种基于投影域数据恢复的低剂量CT优质重建方法。新方法首先通过非线性Anscombe变换将满足Poisson分布的投影域数据转化Gaussian型分布,然后利用针对Anscombe变换的Gaussian型数据进行自适应Block-Matchingand 3D filtering(BM3D)滤波,最后通过对Anscombe逆变换数据执行传统的滤波反投影(Filtered Back Projec-tion,FBP)CT重建。由于Anscombe变换数据的方差已知,且所用BM3D滤波无需人工设置滤波参数,使得方法可实现自适应低剂量CT图像重建。仿真和临床低剂量CT数据的实验表明,方法具有良好的重建鲁棒性,其重建图像的噪声和伪影可同时得到有效抑制。
文摘在处理由椒盐噪声污染的高对比度图像时,使用传统的三维块匹配算法(Block-Matching and 3D filtering,BM3D)去噪不能有效保留图像的边缘和纹理细节,在图像的边缘会出现边缘振铃效应。为了改善传统BM3D算法在处理椒盐噪声时的不足,提出了用边缘方向代替水平方向搜索相似块的BM3D改进去噪算法。实验结果表明,改进BM3D算法获得的相似块数量是传统BM3D算法的3倍,峰值信噪比(PSNR)也得到进一步提高,在去除椒盐噪声的同时也使图像边缘得到有效保留。
