Manish-TMM-(1)

比较反滤波和维纳滤波对一幅图像复原的效果。从两方面出发，一是对运动模糊和均值模糊复原的能力，二是抗噪能力，各种情况分别都进行了对比(Comparison of inverse filtering and Wiener filtering on an image restoration results. Proceed in two ways, first on the motion blur and the mean fuzzy recovery capability and noise immunity, all cases are compared separately)

本程序实现Bilateral滤波，以实现边缘保留的平滑处理，同时可用于灰度及彩色图像。(Bilateral filtering realize this procedure in order to achieve a smooth edge to retain the handle at the same time can be used for gray and color images.)

本程序和实现对一幅包含人脸的bmp图像进行光纤补偿，对人脸区域进行检测实现人眼和人嘴的检测与定位，最后勾绘出人脸的特征以实现人脸检测的目的。(This procedure and implementation of a compensate the fiber contains face of BMP image, the face region detection to realize human eyes and mouth detection and positioning, finally drew out the facial features to achieve the purpose of face detection. )

MATLAB图像处理程序，批量将彩色图片转换成灰色图像，用于其他图像处理程序(MATLAB image processing, batch convert color pictures of the gray image used for other image processing program)

有关pca算法方面的学习，有利于pca算法原理的实现(something related to the study of pca)

本算法一种基于量子遗传算法的图像增强方法，包含多个m子文件。使用量子旋转门(The algorithm based on quantum genetic algorithm of image enhancement methods, contains more than one m subfolders. The use of quantum revolving door)

说明：  ：基于主动轮廓识别和被动轮廓识别方法各自的优缺点，提出结合主动和被动的方法，先对图像进行被动轮廓的预处理，然 后再应用主动轮廓的方法，通过比较选出Canny算子进行预处理，再通过基于概率的方法分割图像，最后再应用Snake模型进行 轮廓提取。并取得较好的应用。(: Identification Based on Active Contour and passive contour recognition advantages and disadvantages of each method, proposed method of combining active and passive, passive first outline of the image pre-processing before applying the active contour method, by comparing the pre-selected Canny operator treatment, and then through the image segmentation method based on probability, and finally application of Snake model for contour extraction. And get better application.)

针对彩色图像的局部直方图均衡化，可以较好的增强图像细节(poshe,it can enhancements the detail of the image )

可对lytro相机所得到的光场图像进行各种处理(The light field image obtained by lytro camera can be processed in various ways.)

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)