radon_detection_test

数字图像处理课程期终项目，对图像进行放大，并进行滤波，达到一定的信噪比。(The final project of the digital image processing lesson, which is programmed for enlarging a image into demanding size.)

很好的倒频谱计算程序，可立即生成图形，方便读者理解运用。(very good。)

USB Composit example for HID

提出一种基于特征点的运动场景图像拼接算法。基于相似变换消除选取在运动物体上的特征点，并使用RANSAC算法进行外点的剔除。在融合阶段，根据齐次变换矩阵求得对2幅图像的差异图像，并执行区域增长算法。从而分割出运动区域。使用一种分段映射算法生成全景图像。实验证明了算法的有效性。(A feature-based algorithm for image mosaics of 8c宅Iles with moving objects is pI．oposcd．The algorithm eliminates the feature points which arc selected in moving objects using similarity transform，and the outliers are eliminated using RANSAC algorithm．In the image blend phase，a difference of two images is created using homogeneous transformation matrix，and a region growth algorithm is implemented SO as to segment the movmg object region．A piecewise mapping algorithm for generating panoramic images is used．Experimental results show the effectiveness of the algorithm．)

实现不规则形状碎纸片的拼接，并展示出原图像(The splicing of irregular shaped pieces of paper is realized and the original image is displayed.)

基础的盲均衡算法，16相位正交调幅恒模盲均衡算法。(A basic blind equlization algorithm ,named as 16 QAM blind equlization for CMA. )

形态学成分分析，该方法的基本思想是利用信号组成成分的形态差异，将图像分割为纹理和分片光滑部分。(Morphological Component Analysis，The basic point is that an image can be divided into texture and piecewise smooth parts by the morphological diversity among signal components.)

根据paper思想，自己编写的SPIHT编解码。可以处理不同图像大小的小波系数，严格按照paper中的算法编写。细节见说明文档(under the paper thinking, their preparation SPIHT codec. Image can handle different sizes of the wavelet coefficients and strictly according to the paper prepared algorithm. For details, see the documentation)

该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）(It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the image patches are gathered according to their similarities.Meanwhile,the similar patches get sparse representation showed in dictionaries by iterative shrinkage and L1 regularization constraints and eventually the image is restored and noise is removed.The experimental results indicate that the proposed algorithm can well preserve the structure information of the common image with a higher Peak Signal to Noise Ratio(PNSR),compared with state-of-the-art algorithms,such as K-SVD and BM3D)

根据icip会议2005年度的一篇文章编写的matlab程序。包含有效果图。 运用smqt（连续均值量化变换）算法进行灰度图像增强。它比传统方法（直方图均衡化处理）的优点在于可以保证增强后图象的直方图波形不变，可以展现图象的底层结构，自动集中改进图象细节。是一种新的效果更好的灰度图象增强算法。(under icip 2005 annual meeting of an article prepared by the Matlab procedures. Includes map results. Smqt use (continuous quantitative mean transform) algorithm for gray-scale image enhancement. It is superior to the traditional method (histogram equalization processing) has the advantage can guarantee enhanced image histogram waveform unchanged. able to display images of the bottom structure, automatic focus on improving image details. Is a new and better results gray image enhancement algorithms.)