SHIF 算法的matlab实现,可以用于比较SHIF算法

robustly fits a fundamental matrix to a set of putatively matched image points.-robustly fits a fundamental matrix to a set of putatively matched image points.

C常用算法 对于初学者，可以参考学习，能够很快入门并掌握一些基础算法-C commonly used method for beginners, you can refer to learn, will soon be started and learn some basic algorithms

用matlab做的基于DCT变换的图像压缩源码，先把图像分成8X8 的子块，然后做DCT变换，再量化，在恢复重建图像-Using matlab to do DCT-based transform image compression source code, first image is divided into 8x8 sub-block, and then make DCT transform, and then quantified, at the resumption of the reconstructed image

dct频域进行图像缩放的源码，非常有用。可以很快的进行图像缩放，免去了DECODE再插值。-DCT frequency domain image scaling for the source, very useful. Can be quickly carried out the image scaling, which eliminates the re-interpolation Decode.

实现图像由rgb到hsi和HSV转换C++代码，hsi-长度为3的双精度数组，rgb- 长度为3的双精度数组-Image from rgb to HSI and HSV conversion C++ Code, hsi-length 3 double precision array, rgb-length 3 double precision array

这是俄罗斯的一个博士的博士论文的配套源码，实现了GRAPH CUT用于立体视觉的匹配，它改善了传统GRAPH CUT计算耗时的缺点，他还因此称为微软一员，专门从事GRAPH CUT在图像处理上的应用。程序写的很精简，写的很好，反复学过很多遍，这也是C/C++爱好者提高编程能力的一个很好的学习样本，很值得仔细反复阅读。-This is a Russian doctoral thesis, Dr. supporting source, realize the GRAPH CUT for stereovision matching, which improves the calculation of time-consuming traditional GRAPH CUT shortcomings, he also is why they are called a Microsoft, which specializes in GRAPH CUT in image processing applications. Procedures written in very concise, well written, repeatedly studied many times before, this is C/C++ Lovers programming ability to enhance a good learning samples, it is worth reading carefully repeated.

Algorithms for images processing-Algorithms for processing images

能实现8位BMP灰度化，二值化的图像处理纯C语言编写的源代码-To achieve 8 BMP gray and binary image processing pure C language source code

高速图像及其小波分解，并用FPGA实现，对做嵌入式图像处理的人员有益。-FPGA,wavelet,

Non-decimated wavelet transform, redundant wavelet transform, stationary ％ wavelet transform-Non-decimated wavelet transform, redundant wavelet transform, stationary wavelet transform