demo

C# 远程打码 实例项目源码

应用于车牌识别中图像增强部分的对比度增强部分！（试了，出的图像效果对比效果比较明显）(License Plate Recognition used in image enhancement part of the contrast enhancement part! (Tried out the effect of the image contrast more obvious))

利用MATLAB自带的两幅RGB彩色图像根据对图像互相关性的分析进行图像配准。(Using two RGB color images MATLAB, image registration is performed based on the analysis of image crosstalk.)

说明：  matlab下的相机标定工具箱，包含角点检测，求取相机内参，误差分析，求相机外参，图像校正等多种功能。附带有实验用的20张图像。(matlab under the camera calibration toolbox, including corner detection, strike the camera restricted reference materials, error analysis, seeking the camera outside the parameters, image correction, multiple functions. Comes with the 20 experimental images.)

本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景 物在不同波段表现的特征也各不相同等问题，提出了基于互信息相似性测度的 多光谱图像配准算法。(In this paper, multi-spectral image registration between images in different spectral gray there is a big difference, the same scene in different performance characteristics of band varies and so on, based on mutual information similarity measure for multi-spectral image registration algorithm .)

ZIGZAG程序，实现对图像矩阵ZIGZAG顺序读取。通常作为函数调用。还有就是霍夫曼编码的程序，得到图像霍夫曼的编码(ZIGZAG procedures ZIGZAG image matrix to achieve the order read. Usually as a function call. There is the Huffman code procedure, the image encoding Hoffman)

说明：  图像处理基于harris角点特征的图像配准程序(Image processing based on the characteristics of harris corner image registration procedures)

基于遗传算法的图像分割算法。实现图像的分割，显示原图及处理结果图像。(Based on genetic algorithm image segmentation algorithm. Realize image segmentation, and processing results show the image. )

对矩形件的排样过程进行编码实现，通过visual c++(layout problem)

Zhang等人 利用相位一致性信息的特性，提出了 特征相似性方法(FSIMG) ，选取了相位一致性信息和梯度信息 作为它的两个特征，得到了较好的结果。 (A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimensionless measure of the significance of a local structure, is used as the primary feature in FSIM. Considering that PC is contrast invariant while the contrast information does affect HVS’ perception of image quality, the image gradient magnitude (GM) is employed as the secondary feature in FSIM. PC and GM play complementary roles in characterizing the image local quality. After obtaining the local quality map, we use PC again as a weighting function to derive a single quality score. Extensive experiments performed on six benchmark IQA s demonstrate that FSIM can achieve much higher consistency with the subjective uations than state-of-the-art IQA metrics.)