saliency_SR

使用选择式掩膜平滑方法进行数字图像的边缘提取(Select the type mask smoothing method using digital image edge extraction)

首先通过多分辨率分解法提取高频边缘，然后分别对每层的高频边缘进行非线性插值得到新的高频边缘，接着对高频边缘进行高通滤波得到等强后的高频边缘，最后对增强后的高频边缘进行修正。再在对增强的图像进行对比度拉伸，从而达到增强的目的！(First of all, through the extraction of multi-resolution decomposition of high-frequency edge, and then were on the edge of each high-frequency non-linear interpolation to be the new high-frequency edge, and then the edge of the high-frequency high-pass filter to be strong, such as after the high-frequency edge, and finally on the brink of enhanced high-frequency be amended. Again in contrast enhanced image stretching, so as to achieve the purpose of enhancing!)

说明：  完成基于各向异性的自适应超声图像去噪和边缘增强方法，参考Adaptive Anisotropic Diffusion for Ultrasonic Image Denoising and Edge Enhancement.pdf，加入了m参数(The completion of ultrasound-based adaptive anisotropic image denoising and edge enhancement method, reference Adaptive Anisotropic Diffusion for Ultrasonic Image Denoising and Edge Enhancement.pdf, joined the m parameters)

在高斯混合噪声背景下实现SLIM谱估计算法和l1范数SLIM谱估计法，并在-5到15的信噪比条件与CRLB对比均方频率误差(the paper achieves the SLIM spectral estimation algorithm and l1-SLIM spectral estimation method under the Gaussian mixture background noise,then compares the mean square frequency error with CRLB under SNR from-5 to 15 )

通过纹理方向估计消失点，通过消失点来检测道路区域。 该程序应用到了基于纹理的张量投票算法来估计消失点；通过纹理方向和颜色信息，生成用于估计两个最主要道路边界的直方图；最后将道路区域定义为两个检测到的道路边界之间且低于估计的消失点的区域(The vanishing point is estimated by the texture direction, and the road area is detected by the vanishing point. The program applies a texture-based tensor voting algorithm to estimate the vanishing point; through the texture direction and color information, generates a histogram for estimating the two most important road boundaries; finally defines the road area as two detected road boundaries. An area between and below the estimated vanishing point)

基于SVD和混沌加密的DWT。程序里包含了直方图攻击，锐化，剪切，高斯噪声等攻击。(Based the SVD and chaotic encryption DWT. The program contains a histogram attack, sharpening, shear, Gaussian noise attack.)

图像匹配最新的源码 matlab 适合初学者和进阶者作者hongshengli (The latest source of image matching matlab for beginners and advanced by Author hongshengli)

基于随机Hough变换的圆检测方法，可检测不同位置、半径的圆。(Based on random Hough transform circle detection method can detect a different location, the radius of the circle.)

奇异值分解波束形成，自适应波束形成仿真。由均匀线阵形式，确定阵列的导向矢量；由阵列导向矢量，对接收信号进行建模仿真；根据约束条件，实现自适应波束形成算法；考察算法性能与信噪比，采样率，观测时间等参数的关系。 (SVD beamforming, adaptive beamforming simulation. Form by the ULA to determine the array steering vector by the array steering vector, the received signal modeling and simulation under constraint conditions, adaptive beamforming algorithm examine algorithm performance and signal to noise ratio, sample rate, observation time, etc. parameters.)

高斯列主元消去法，用来解多元线性方程组，从而解决相关的方程组问题(Principal component Gaussian column elimination method used to solve a multivariate linear equations to solve the equations)