Imageprocessing

matlab实现区域生长算法。实现起来很简单，操作起来很方便。()

利用Artoolkit实现了虚拟现实的算法，VS2008下测试通过(Use Artoolkit algorithm to achieve a virtual reality, VS2008 under test)

图像分割，包括阈值分割Otsu法，边缘检测包括Roberts算子，Canny算子等，边界跟踪包括Bwtraceboundary函数调用来对图像进行分割等(Image segmentation, including threshold segmentation method of Otsu edge detection, including Roberts operator, Canny operator, edge tracking includes Bwtraceboundary function calls to the segmentation of the image)

单尺度SSR(Single Scale Retinex)(A Retinex Function)

infomax ICA的算法实现，并在其中给出了一个infomax ICA的算法用于图像边缘检测的例子(infomax ICA algorithm, which gives an infomax ICA algorithm for image edge detection example)

《智能图像处理技术》——由李弼程等编写，区别于大多传统的图像处理技术书籍，该书主要讨论了图像处理的最新发展，如图像的特征分析、配准、融合、分类等技术，具有前沿性和先进性( Intelligent image processing technology - such as prepared by Bicheng, mostly from the traditional image processing technology books, the book discusses the latest developments in image processing, such as the characteristics of image analysis, registration, integration, classification and other technology, having cutting-edge and advanced)

非常好的纹理分割，区域分割的matlab源代码，可用(Very good texture segmentation, region segmentation matlab source code can be used)

通过统计直方图并作相应的处理完成了红外图像非均匀性校正，特别是针对红外图像中常见的条纹非均匀性(Through statistical histogram and processed accordingly infrared image non-uniformity correction, especially for the common striped infrared image non-uniformity)

网格简化， 将复杂的带有很多细节的物体的三维立体网格进行任意比例的简化，使得其减少点和面片的数量并保持物体的基本特征，以达到加快图像显示及压缩文件的效果。(Mesh simplification, the complex three-dimensional grid with many of the details of the object simplified in any proportion, such that it reduce the number of points and surfaces of the sheet and keep the basic characteristics of the object, in order to achieve the speed up of the image display and the effect of the compressed file .)

本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。 现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。 通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。 (This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious. Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults. Throug)