Description: SVD去噪，构造的矩阵方法为对数据进行均匀分段，并对去噪前后的信噪比，均方差进行了对比。-SVD denoising, construction of the matrix method for the data sub-uniformity, and signal to noise ratio before and after denoising are compared variance. Platform: |
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Author:李冰 |
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Description: 摘要:为了提高图像复原算法的性能 ,提出了一种改进的奇异值分解法估计图像的点扩散函数。从图像的退化离散模型
出发 ,对图像进行逐层分块奇异值分解 ,并自动选取奇异值重组阶数以减少噪声对估计的影响。利用理想图像奇异值向
量平均能谱指数模型 ,估计点扩散函数奇异值向量的频谱 ,再反傅里叶变换得到其时域结果。实验结果表明 ,该方法能
在不同信噪比情况下估计成像系统的点扩散函数 ,估计结果比原有估计方法有所提高 ,有望为图像复原算法的预处理提
供一种有效的手段。-Abstract : To improve the performance of image restoration algorithms , a modified Singular Value De2
[ ] [ ]
composition SVD method was proposed to estimate the Point Spread Function PSF of an imaging
system. Using the discrete image degradation model , a block2based SVD filter scheme was applied for
the image denoising with an automatically determined singular value rank. After the spectra of PSF
singular vectors were estimated under an exponential model for the averaged spectra of un2degraded
image singular vectors , the IFFT was used to get the time2domain estimation of the PSF. The experi2
mental results show that this proposed method can be applied to estimate the PSF of the imaging sys2
tem under a wide SNR range and its performance is better than the original method. It may be used as
an effective method for the image preprocessing in image restoration problems.
[ ]
Key words: image restoration Point Spread Function PSF block2based Singular Value Decomposi2 Platform: |
Size: 476160 |
Author:zy |
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Description: 自适应估计SVD分解收缩值的算法， 在自然影像医学影像去噪中有重要应用-A practical algorithm，adaptive to select the thresholding values and applied to image and signal denoising Platform: |
Size: 6144 |
Author:贺威 |
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Description: An adaptive image denoising technique based on
the nonlocal means (NL-means) algorithm is investigated in this
research. The proposed method first employs the singular value
decomposition (SVD) method and the K-means clustering (Kmeans)
technique for robust block classification in noisy images.
Then, the local window is adaptively adjusted to match the local
property of a block. Finally, a rotated block matching algorithm
is adopted for better similarity matching. Experiment results are
given to demonstrate the superior denoising performance of the
proposed adaptive Platform: |
Size: 1118208 |
Author:杨松 |
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Description: 实现图像的稀疏编码，采用k-svd进行字典学习，omp算法进行稀疏表示系数的计算，内附有去噪例子(To achieve the image sparse coding, using K-SVD dictionary learning, OMP algorithm for sparse representation of the calculation of factors, with examples of denoising) Platform: |
Size: 2048 |
Author:chenchenchen...
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Description: 基于K-SVD方法的图像去噪算法，代码是MATLAB版的(Image denoising algorithm based on K-SVD method, the code is MATLAB version of) Platform: |
Size: 37888 |
Author:teslahua
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Description: 调用程序可对信号进行EMD分解，再进行奇异值分解降噪(The calling program can decompose the signal by EMD, then the singular value decomposition and denoising 2D empirical wavelet program. The calling subroutine can perform the empirical wavelet transform on the image.) Platform: |
Size: 24576 |
Author:安之若素_ |
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