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图像超分辨率重构
Image Super-Resolution as Sparse Representation of Raw Image Patches-Image Super-Resolution as Sparse Representation of Raw Image Patches
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一种图像处理超分辨率重构方法,主要是利用图像稀疏表示的方法进行图像重构-Super-resolution reconstruction of an image processing method, mainly using sparse representation of image reconstruction methods for image
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强壮的人脸识别系统,发表于cvpr2011年,程序是应用matlab实现-Recently the sparse representation (or coding) based classifi cation (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as
a sparse linear combination of the trai
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图像稀疏编码的一种方法,可用于基于稀疏表示的图像压缩、去噪等-Sparse image coding method can be used for sparse representation-based image compression, denoising, et
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关于图像稀疏表示的鲁棒掌纹处理,在国内很少有基于稀疏的掌纹处理文章-Robust sparse representation on the palm print image processing, very few in the country' s palm with posts based on sparse
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人脸识别的稀疏表示识别方法将稀疏表示的保真度表示为余项的L2范数,但最大似然估计理论证明这样的假设要求余项服从高斯分布,实际中这样的分布可能并不成立,特别是当测试图像中存在噪声、遮挡和伪装等异常像素,这就导致传统的保真度表达式所构造的稀疏表示模型对上述这些情况缺少足够的鲁棒性。而最大似然稀疏表示识别模型则基于最大似然估计理论,将保真度表达式改写为余项的最大似然分布函数,并将最大似然问题转化为一个加权优化问题-Recently the sparse representation (or codin
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用基于稀疏表示和KSVD字典学习去噪方法在对数域对SAR图像抑斑,本方法相对于一些经典的SAR图像抑斑方法,抑斑效果大大提高。-Based on the sparse representation and KSVD dictionary learning denoising method in the logarithmic domain,we despeckle SAR image, compared with some of the classic SAR image speckle sup
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低秩矩阵与稀疏表示应用,大致的介绍了低秩矩阵与稀疏表示在图像处理以及其他领域的作用-Low-rank matrix and sparse representation of the application, the approximate low-rank matrix and sparse representation in image processing and other areas
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一种利用中心和结构聚类的稀疏表示图像去噪方法,有不错的效果-a image denoising method with structral clustering and sparse representation, has good effect .
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基于类别相关近邻子空间的最大似然稀疏表示鲁棒图像识别算法-Category neighboring subspace-based maximum likelihood sparse representation robust image recognition algorithm
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正交匹配追踪是压缩感知中重建算法的一种,能够以高概率重建原始信号-Image Denoising Via Learned Dictionaries and Sparse representation
Image Denoising Via Learned Dictionaries and Sparse representation
Image Denoising Via Learned Dictionaries and Sparse representation
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通过稀疏表示图像超分辨率(TIP2010)-Image Super-Resolution via Sparse Representation(TIP2010)
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此程序,是应用在压缩感知方面的稀疏表示,图像重构。程序中利用现在流行的CS理论,在采样率为0.9时,成功的实现了图像重构-This procedure is used in the compressed sensing aspects of sparse representation, image reconstruction. Program using the now popular CS theory, the sampling rate is 0.9, the successful re
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Image Super-Resolution via Sparse Representation.pdf
通过稀疏表示算法实现图像的超分辨率表示。
稀疏表示算法主要用在图像去噪图像恢复上,是一个很好的工具。-Image Super-Resolution via Sparse Representation.pdf
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KSVD用于稀疏字典的训练,稀疏表示用于图像去噪-An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
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这篇文章主要是讲高光谱分类的,使用基于词典的稀疏算法对高光谱进行分类。-Dictionary-Based, Clustered Sparse Representation for
Hyperspectral Image Classification
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图像去噪修复的典型算法代码包,包含基于稀疏表示的KSVD图像去噪,BM3D彩色图像去噪代码,TV图像修复代码,MCA图像修复代码。(Typical image denoising algorithm code package, including sparse representation based on KSVD image denoising, BM3D color image denoising code, TV image restoration code, MCA image res
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利用稀疏表示原理来进行单幅影像超分辨重建(use sparse representation to single image super resolution)
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Nonlocally Centralized Sparse Representation
for Image Restoration
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杨建超的将稀疏表达用于图像超分辨率重建的文章赋代码(Example matlab code for the algorithm proposed in "Image super-resolution via sparse representation" TIP 2010.)
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