workspace03_PSNR

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)

说明：  利用ikmeans算法实现图像分割matlab代码(ikmeans algorithm to deal image segmentation)

此算法用于对图片进行光照补偿，并对补偿前后的图片进行对比。(This algorithm is used for illumination compensation, and compensation before and after pictures comparing picture.)

matlab 实现暗通道去雾算法 根据cvpr论文改编(matlab channel to achieve the dark fog adaptation algorithm based on cvpr papers)

采用相邻一定距离的邻域图像差，提高了抗干扰能力，对亮度变化不敏感(Matching based on neighborhood difference feature)

一种鲁棒性较强的提高图像阴影区域质量的图像增强技术，LITAO(A Robust Image Enhancement Technique for Improving Image Visual Quality in Shadowed Scenes)

用于信号特征提取、信号消噪，MinkowskiMethod算法 ,未来线路预测,分析误差。( For feature extraction, signal de-noising, MinkowskiMethod algorithm, Future line prediction, error analysis.)

通过PCL点云库对点云数据进行三维重建的好例子

P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理 (P0301: digital image data matrix display and Fourier Transform P0302: two-dimensional discrete cosine transform image compression P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization P0305: Simulation images by white Gaussian noise and salt and pepper noise P0306: 2D median filtering function medfilt2 right by Salt and Pepper image noise filtering P0307: using MATLAB functions filter2 of noise images mean filtering P0308: Image Adaptive Filter Weiner P0309: use five different gradient Enhancement Act for image sharpening P0310: Images of the high-pass filtering and mask handling P0311: use Butterworth (Butterworth) low-pass filter on the noise in the image smoothing P0312: use Butterworth ( Butterworth) high-pass filter for image sharpening)

NEDI源代码，是用于超分辨率重建的，并附上原文献，希望对大家有用~(The NEDI source code for super-resolution reconstruction, together with Uehara literature, we want to ~)