Description: 对于一些图像来说，常用的边缘检测算法有时候无法设立合适的阈值将它们的梯度较小的模糊边缘检测出来。为了解决这个问题，有两种解决方法：将图像方差标准化，拉大模糊边缘的梯度值，或通过设置sigmoid函数，将像素所在区域的信息传递到梯度值中去，对其进行调整，就能找到合适阈值，有效地将模糊边缘提取出来。本程序把这两种算法实现并与与传统算法进行了比较。-For some images, the commonly used edge detection algorithm sometimes can not be an appropriate threshold for the gradient of their smaller fuzzy edge detected. To solve this problem, there are two solutions: the image variance standardization, widening the fuzzy edge of the gradient value, or by setting the sigmoid function pixel region to disseminate the message to the gradient values to adjust, on the can find a suitable threshold, effectively extracted fuzzy edge. This procedure of these two algorithms with the traditional algorithm. Platform: |
Size: 1024 |
Author:李思齐 |
Hits:
Description: Eigenfaces: PCA tends to find a p-dimensional subspace
whose basis vectors correspond to the maximum
variance direction in the original image space (p N).
We called the new subspace defined by basis vectors “face
space”. First, all training faces are projected onto the face
space to find a set of weights that describes the contribution
of each vector. Then we project all testing faces onto the
face space to obtain a set of weights. Finally, we identify
the face by comparing a set of weights for the testing face
to sets of weights of training faces. Platform: |
Size: 7017472 |
Author:sam |
Hits:
Description: Eigenfaces: PCA tends to find a p-dimensional subspace
whose basis vectors correspond to the maximum
variance direction in the original image space (p N).
We called the new subspace defined by basis vectors “face
space”. First, all training faces are projected onto the face
space to find a set of weights that describes the contribution
of each vector. Then we project all testing faces onto the
face space to obtain a set of weights. Finally, we identify
the face by comparing a set of weights for the testing face
to sets of weights of training faces. Platform: |
Size: 11264 |
Author:sam |
Hits:
Description: 最大类间方差法是图像分割中一种常用的阈值分割方法, 对于单阈值分割具有显著的效果, 但是对于
多阈值分割, 计算复杂度大、耗时较多。本文将粒子群优化算法与最大类间方差法结合, 提出了一种新的图像分
割方法, 该方法利用粒子群优化算法的寻优高效性, 并由灰度图像的最大类间方差值作为适应值, 搜索最优分割
阈值, 实现图像的多阈值分割。实验结果显示, 新方法大大缩短了寻找最优阈值的时间, 降低了运算复杂度, 提
高了图像分割速度, 说明基于粒子群优化算法的图像分割算法是可行的、有效的。-Maximum between-class variance method is a popular image segmentation threshold segmentation method has a significant effect for the single-threshold segmentation, but
The multi-threshold segmentation, the computational complexity of large, time-consuming. In this paper, particle swarm optimization combined with maximum between-class variance method, a new image
Cut method, the method using particle swarm optimization algorithm optimizing the efficiency of the maximum between-class variance by the gray-scale image as the fitness value, search for the optimal split
Threshold, multi-threshold image segmentation. The experimental results show that the new method greatly shorten the time to find the optimal threshold, reducing the computational complexity, to mention
The high speed of image segmentation, image segmentation algorithm based on particle swarm optimization algorithm is feasible and effective. Platform: |
Size: 313344 |
Author:张泰然 |
Hits:
Description:
Wavelet denoising
For using this code need to use signal toolbox and general toolbox in your matlab
In the first part of this assignment, we asked to obtain a (black-and-white) digital image of size
512 by 512 and then generate noisy image by adding a Gaussian noise but under the condition of
having SNR=20dB by select the suitable value of variance for Gaussian noise formula.
Second step is performing wavelet denoising using the hard thresholding (Use the db 6 for four
levels) in the condition of finding the optimal thresholding value of T in terms of the SNR obtained. It
means that, we should find the highest SNR value by finding the suitable value for threshold. Then we
asked to do the same process but this time using soft thresholding.
Finally for the last part of question one, we should compare the results of the obtained SNR
with the recommendations of 3*sigma for the hard thresholding and 3/2*sigma for the soft
thresholding.-
Wavelet denoising
For using this code need to use signal toolbox and general toolbox in your matlab
In the first part of this assignment, we asked to obtain a (black-and-white) digital image of size
512 by 512 and then generate noisy image by adding a Gaussian noise but under the condition of
having SNR=20dB by select the suitable value of variance for Gaussian noise formula.
Second step is performing wavelet denoising using the hard thresholding (Use the db 6 for four
levels) in the condition of finding the optimal thresholding value of T in terms of the SNR obtained. It
means that, we should find the highest SNR value by finding the suitable value for threshold. Then we
asked to do the same process but this time using soft thresholding.
Finally for the last part of question one, we should compare the results of the obtained SNR
with the recommendations of 3*sigma for the hard thresholding and 3/2*sigma for the soft
thresholding. Platform: |
Size: 91136 |
Author:jams1166 |
Hits:
Description: 本文提出一种基于图像分辨率的自适应分层式图像平滑算法。首先对每个像素在不同分辨率窗口下平滑处理，然后找出该像素被判断为同质区域下的最大窗口，在此，判断方法为比较其同质度和全局鲁棒估计方差的大小。在平滑处理过程中，对同质区域和纹理域分别采用不同算法处理。-This paper presents an adaptive hierarchical image resolution image smoothing algorithm. First, for each pixel smoothing window at different resolutions, and then find the pixel is judged to be the largest homogeneous area under the window, where, judging by comparing their degree of homogeneity and the size of the global robust variance estimation. In the smoothing process, homogeneous regions and textures using different domain algorithm processing. Platform: |
Size: 1276928 |
Author:沉稳 |
Hits:
Description: 噪声发生器
查找（或开发）将高斯噪声添加到图像的程序。您必须能够指定噪声均值和方差。(1.Noise Generators
This is a generic project, in the sense that the programs developed here are used in several of the projects that follow. See Fig. 5.2 for the shapes and parameters of the following noise probability density functions.
(a) Find (or develop) a program to add Gaussian noise to an image. You must be able to specify the noise mean and variance.) Platform: |
Size: 208896 |
Author:seayon
|
Hits:
Search - find variance for image