StereoDisparity

有关改良Canny算法的一些还算可以的文献(Improved Canny algorithm on some literature.)

说明：  这是“Implicit Active Contours Driven by Local Binary Fitting Energy”（简称LBF模型）的MATLAB源代码。LBF模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。(This is the "Implicit Active Contours Driven by Local Binary Fitting Energy" (referred to as the LBF model) of the MATLAB source code. LBF model is very important to local area active contour model, which is widely used in various fields, such as MRI brain image segmentation, vessel segmentation, image bias field correction.)

极化SAR图像处理，经典的Lee滤波处理，可实现sar图像的去除斑点噪声处理(SAR image filtering based on Lee s algorithm.)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

镜头指纹识别，提取镜头特征，对其他照片进行识别，判断是否来源同一相机。(Image Source Detection)

matlab 车牌识别，含有gui界面，边缘检测车牌定位，神经网络字符识别(Matlab license plate recognition, including GUI interface, edge detection, license plate location, neural network, character recognition)

图片雾化效果 实例

说明：  前馈神经网络图像去噪，DnCNN的MATLB实现，以及相应的峰值信噪比和结构相似性的计算。(DnCNN,MATLAB,And calculation of peak signal-to-noise ratio structural similarity)

第8章 图象的检测及模板匹配 图象的分割与检测(识别)实际上是一项非常困难的工作。很难说清楚为什么图象应该分割成这样而不是那样。(Chapter 8 Detection of image template matching and image segmentation and detection (recognition) is actually a very difficult task. It is hard to say clearly why the image should be divided into such and not as.)

多边形填充 多边形裁剪 自定义多边形区域 自定义裁剪区域(Polygon fill polygon clipping custom polygon area custom crop area)