cvpr09-(matlab)

使用Splitting算法和GLA算法实现对图像的矢量量化及重新编码和重建。(Vector Quantization:To generate a 16-codeword codebook using Splitting Algorithm and GLA,then use this codebook to code the training image and reconstuct it.)

线性CCD大津动态自适应阈值二值化源程序(Linear CCD dynamic adaptive threshold binarization dajin source program)

蚁群算法实现医学图像的分割，同时对比FCM算法，非常有用，可以直接运行，包含测试MRI图片(Ant-Colony algorithm for MRI image segmentation including MRI image for testing.)

这是细胞边缘检测和找出细胞轮廓线的功能代码，可以很好的对细胞进行分割(This is the cell edge detection and contour lines to identify cell function code, a good division of cells)

视觉引导车路识别：灰度AGV路径识别；彩色AGV路径识别；HSI彩色空间的AGV路径识别；路径中心线的定位；Radon变换的AGV路径偏差检测(Vision Guided Vehicle Road Identification: gray AGV path identification color AGV path identification HSI color space of the AGV path identification path centerline positioning Radon transform of the AGV path deviation Detected)

说明：  傅里叶变换中的角谱衍射理论，GS算法实现(Angle spectrum diffraction theory in Fourier transform, Realization with GS algorithm)

chan和vese的多水平集算法，可以用2条初始水平集来演化，从而达到检测多目标的目的。(chan and the multi-level set algorithm, you can use two sets to the initial level of evolution, so as to achieve the goal of multi-purpose.)

说明：  迭代收缩阈值算法和快速收缩阈值迭代算法求解Lasso问题(Iterative Shrinkage Thresholding Algorithm (ISTA) for LASSO problem)

手机软板自动检测的图像预处理及分割方法(FPC phone automatically detects the image preprocessing and segmentation methods)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)