10257131SupResolDemo

采用MATLAB语言编程实现了基于遗传算法的最大熵单阈值、最大熵双阈值、二维最大熵单阈值图像分割和基于最大类间方差遗传算法的图像分割(Through the study of threshold segmentation method and genetic algorithm theory, matlab programming language used to achieve the genetic algorithm based on maximum entropy single threshold, dual-threshold maximum entropy, maximum entropy of two-dimensional single-threshold image segmentation and otsu genetic algorithm for image segmentation.)

求图像的二维直方图，产生共生矩阵，可以比较像素点分布的是否均匀。(Two dimensional histogram for image, the co-occurrence matrix, can compare the pixel distribution is uniform.)

这个算法包实现了从多幅拥有共同结构的图像里提取出共同形状的骨架。( This package implements the algorithm for Sketching the Common as described in: Shai Bagon, Or Brostovsky, Meirav Galun and Michal Irani "Detecting and Sketching the Common", CVPR 2010)

说明：  彩条产生程序。。。。720p需添加74.25M时钟(colorbar generation. need 74.25mhz clock if 720p gen)

Edge preservation measure Index: Pratt s Figure of Merit

Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image.

介绍qbic图像处理工具的详细文档，如有兴趣请看看(Introduction qbic detailed documentation of image processing tools and, if interested please take a look)

说明：  利用线性规划问题求解稀疏恢复问题的基追踪（basis pursuit，BP）算法，研究了在含有脉冲噪声干扰的原始信号环境下对经典基追踪算法的改进。(basis pursuit (BP) algorithm)

用于单目标追踪的多模概率假设粒子滤波程序(MM-PHD for single target)

给定一副图像，采用一定的策略对其进行搜索以确定其中是否含有人脸，如果是则返回一脸的位置、大小和姿态(人脸检测)