Roma_MATLAB

这是一个关于图像处理的程序，能够将像素比较低的图像变成分辨率高的图像.(This is a matter of image processing procedures, can be relatively low-pixel high resolution image into the image.)

实现bmp位图的图像放大缩小，包含整个mfc的源码文件。(Achieve bmp bitmap image zoom, contains the entire mfc source files.)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

图像显著性，利用Itti视觉显著性分析算法，提取视觉对输入图像的感兴趣部分(Image salient regions)

说明：  基于matlab平台计算一副图像的信息熵(Calculate the entropy of an iamge using matlab)

数字图像处理(冈萨雷斯)书中的边界链码实现,该程序通过取网格,简化了编码的数据量(Digital image processing (Gonzalez) the boundary chain code book, realize that the procedures through access grid, simplifying the coding of data)

此文档中的代码可以计算5种图像的质量参数，分别是：图像灰度均值、图像方差、图像平均梯度、熵和峰值信噪比及均方误差。(The code in this document can be calculated five kinds of image quality parameters, namely: the image gray value, image variance, average gradient image, entropy and peak signal to noise ratio and mean square error.)

DELPHI编写灰度直方图显示，DELPHI编写灰度直方图显示(DELPHI Writing gray histogram display, DELPHI written grayscale histogram display)

基于马尔可夫随机场(MRF)、条件迭代算法ICM的图像分割源码(The MRF, the ICM-based image segmentation source code to source image segmentation based on the MRF ICM)

说明：  另外一种有效的椭圆陪陪技术，对于亚像素边缘检测非常有用的，真的不错(Oval to chat with another kind of effective techniques for sub-pixel edge detection is very useful, really good)