Description: 在使用扩散过程平滑噪声之后引入反扩散过程来恢复边缘，结合尺度空间理论和反扩散函数对图像进行去噪处理。该方法使用最小描述长度(MDI )准则自适应地选择图像中每一点处的最优尺度对图像进行滤波。加入尺度范围限制降低了过平滑和欠平滑的影响。改进了反扩散函数模型，对降质图像中的边缘进行恢复。与经典的滤波方法以及各向异性扩散方程的结果相比。本文方法取得了较好的效果。-Diffusion process in the use of noise after smoothing the introduction of anti-diffusion process to restore the edge, combined with scale space theory and the anti-spread function of image denoising treatment. This method is the use of minimum description length (MDI) criteria for adaptive selection of images every point in the Agency Platform: |
Size: 225280 |
Author:liqiangqiang |
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Description: 利用matlab语言在各向异性扩散算法基础上实现的边缘检测算法。含参考文献（pdf格式）：
Scale-Space and Edge Detection Using Anisotropic Diffusion.pdf
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 12. NO. 7. JULY 1990-Matlab language use in the anisotropic diffusion algorithm based on edge detection algorithm. Containing References (pdf format): Scale-Space and Edge Detection Using Anisotropic Diffusion.pdfIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 12. NO. 7. JULY 1990 Platform: |
Size: 1159168 |
Author:forestnie |
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Description: 包括图像分析的四部分代码：matlab扩散和高斯函数，线性扩散，线性复扩散，非线性扩散。-It contains four parts：
[1]MATLAB function:diffusion.m gauss.m
[2]Linear diffusion
Applying linear diffusion to images creating linear scale-space.
MATLAB code: demo_lin.m
Image: haifa1.bmp
[3]Linear complex diffusion
Applying linear complex diffusion creating Gaussian and Laplacian scale-spaces. MATLAB code: demo_cmplin.m
[4]Nonlinear diffusions:
Perona-Malik ["Anisotropic diffusion"]
Catte et al. regularization of P-M
Complex ramp-preserving diffusion
Nonlinear edge preserving diffusions.The classical Perona-Malik process: the value of the diffusion coefficient is reduced near edges estimated by the first derivative. Best applied to step edges. A regularized version by Catte et al- the gradient estimation for controlling the process is smoothed by a Gaussian. Proved to be mathematically well-posed. Ramp preserving complex diffusion- best for ramp-type edges. Results are smoother with almost no staircasing effects.
MATLAB code: demo_nldif.m
Image: ct_scan.bmp Platform: |
Size: 239616 |
Author:吴豪科 |
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Description: 图像在传输过程中，传递函数对高频成分有衰减作用，造成图像模糊，细节轮廓不清楚。图像锐化就是补偿图像的轮廓，增强图像的边缘及灰度跳变的部分，使图像变得清晰。亦分空域处理和频域处理两类[3]。-Image in the transmission process, the transfer function of the role of high frequency components are attenuated, resulting in image blurring, the details of the outline is not clear. Image sharpening is the outline of the image compensation, edge enhancement and gray-scale image of the hopping part of the image became clear. Also sub-space and frequency domain processing to deal with two types of [3]. Platform: |
Size: 171008 |
Author:王瑜 |
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Description: 在图象中，边缘是由灰度级和相邻域点不同的象素点构成的。因而，若想增强边缘，就应该突出相邻点间的灰度级的变化。微分运算可用来求信号的变化率，因而具有加强高频分量的作用。如果将其应用在图象上，可使图象的轮廓清晰。由于我们常常无法事先确定轮廓的取向，因而挑选用于轮廓增强的微分算子时，必须选择那些不具备空间方向性的和具有旋转不变的线形微分算子。-In the image, the edge is adjacent to the gray-scale and different domains consisting of the pixel points. Thus, if the edge enhancement, it should highlight the points between adjacent gray-scale changes. Differential operator can be used to signal changes in the rate of demand and thus to strengthen the role of high-frequency component. If the images on their application, will enable a clear outline of the image. Since we often can not be pre-determined orientation of the outline, so the selection for the differential operator to enhance the outline of midnight, to choose those who do not have the space and the direction of rotation-invariant linear differential operator. Platform: |
Size: 1024 |
Author:宇航 |
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Description: 含有了图像处理中一些经典和常用的图像处理算法，如：灰度图像处理，图像增强，图像变换，形态学图像处理。其中灰度图像处理包含三个算法：彩色图转灰度图，灰度图直方图，直方图均衡化；图像增强含有：增加椒盐噪声，中值滤波，sobel算子边缘提取(水平方向和垂直方向一起考虑)，laplace算子边缘提取，模糊，锐化；图像变换含有：haar小波变换，RGB转HSV颜色空间。形态学图像处理含腐蚀，膨胀，开操作，闭操作。-Contains some of the classic image processing and image processing algorithms commonly used, such as: gray-scale image processing, image enhancement, image transformations, morphological image processing. One gray-scale image processing consists of three algorithms: color map turn gray level, gray level histogram, histogram equalization image enhancement includes: Increasing Salt and pepper noise, median filtering, sobel edge detection operator (horizontal and vertical the direction considered together), laplace operator edge detection, blur, sharpen image transformation includes: haar wavelet transform, RGB switch to HSV color space. Morphological image processing, including corrosion, swelling, open operation, closed operation. Platform: |
Size: 317440 |
Author:孙亚新 |
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Description: Perona和Malik在热传导方程的基础上，建立了各向异性扩散方程并将其应用到了图像处理中尺度空间的图像平滑上，该模型针对图像的边缘部分和非边缘部分进行不同性质的图像处理，同时解算方程的迭代格式简单，克服传统滤波的主要缺陷，是图像质量大为改善，为图像的边缘检测和增强开辟了新的方向。-Perona and Malik in the heat conduction equation based on an anisotropic diffusion equation and its application to image processing in scale space of image smoothing on the edge of the model for the image part and the non-edge parts of the different types of image processing, also calculate the iterative equation is simple, to overcome the major shortcomings of traditional filtering is much improved image quality for image edge detection and enhancement to open up a new direction. Platform: |
Size: 11999232 |
Author:苏白龙 |
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Description: SIFT 由特征提取，特征描述符描述和特征匹配 3 部分构成，该算子特征提取数目庞大，建立特征描述符运算
量高，导致算法效率低。提出了一种 SEC( SIFT-Edge-Corner) 算法，在图像尺度空间提取角点代替 SIFT 特征点，并根
据角点是边缘曲率极值理论，预先采用 Canny 算子得到高斯边缘图像金字塔，再提取角点并进行尺度选择。实验结
果表明: 该算法在保障高准确率的前提下大幅度提高特征提取效率-By the SIFT feature extraction, feature descriptions and feature matching descriptors 3 parts, the large number of feature extraction operator established feature descriptor computation high, resulting in low efficiency of the algorithm. Presents a SEC (SIFT-Edge-Corner) algorithm, the image scale space instead of SIFT feature extraction corner points and corner points based on extreme value theory is an edge curvature in advance using Canny operator edge image obtained Gaussian pyramid, and then extract corner point and scale selection. Experimental results show that: the algorithm protect high accuracy under the premise of feature extraction efficiency greatly improved Platform: |
Size: 231424 |
Author:焦婷 |
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Description: The aim of this paper is to describe a novel and completely
automated technique for carotid artery (CA) recognition,
far (distal) wall segmentation, and intima–media thickness (IMT)
measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima-The aim of this paper is to describe a novel and completely
automated technique for carotid artery (CA) recognition,
far (distal) wall segmentation, and intima–media thickness (IMT)
measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale–space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen–intima Platform: |
Size: 2934784 |
Author:suhail |
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Description: HOG即histogram of oriented gradient, 是用于目标检测的特征描述子，该技术将图像局部出现的方向梯度次数进行计数，该方法和边缘方向直方图、scale-invariant feature transform类似，不同的是hog的计算基于一致空间的密度矩阵来提高准确率。Navneet Dalal and Bill Triggs首先在05年的CVPR中提出HOG，用于静态图像or视频的行人检测。-HOG i.e. histogram of oriented gradient, is used to describe the characteristics of the sub-object detection, the driving frequency and the technique of local image gradient appeared was counted, and the edge direction histogram method, scale-invariant feature transform is similar, except that the hog consistent with the calculation based on the density matrix of space to improve accuracy. Navneet Dalal and Bill Triggs HOG first proposed in 2005 in the CVPR for still images or video pedestrian detection. Platform: |
Size: 1754112 |
Author:王飞 |
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Description: This a MATLAB implementation of the SIFT keypoint detector and descriptor -do_gaussian: generate Gaussian scale space of input image
do_diffofg: generate Difference of Gaussian (DoG) scale space
do_localmax: local extrema as the potential keypoints
do_extrefine: refine the keypoints by discarding the ones with low contrast and along an edge
do_orientation: compute the orientation of a support region of keypoint
do_descriptor: compute the descriptor of a keypoint based on image gradients.
do_match: match two images based on the nearest neighbor principle and spatial consistency.
do_sift: generate the SIFT descriptors for a given input image. It basically s all the functions above.
Platform: |
Size: 1257472 |
Author:崔雪红 |
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Description: Anisotropic Diffusion Filter to C,
Scale-Space and Edge Detection using Anisotropic Diffusion
Pietro Perona and Jitendra Malik
IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 12, NO. 7, JULY 1990 Platform: |
Size: 41984 |
Author:Skai
|
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Search - scale space and edge