FCM-C-mean-cluster-segment-[matlab]

基于数字图像处理的车型检测,介绍检测车型的方法(Models based on digital image processing detection, vehicle detection method introduced)

打开24位彩色bmp文件, 显示该图像 将图像内容顺时针旋转90度后显示出来 将图像分成等大小的4块，将第1和第3块像素互换后保存 将旋转后的图像转换成灰度图像显示，并保存 对灰度图像求Sobel边缘图，显示出来，并保存 对灰度图像进行Gaussian平滑，并保存（需要体会平滑的作用） 对灰度图像进行2值化(Open 24-bit color bmp files, displays the image will rotate clockwise image content displayed image is divided into four equal-sized 90 degrees, the first and three pixels after swap to save the rotated image conversion ashes of the image display, and save images to grayscale seeking Sobel edge map is displayed, and save the gray image Gaussian smoothing, and save (experience required smoothing effect) grayscale image binarized)

论文《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》提出的算法代码(algorithm code of pape《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》)

图像处理技术边缘检测源码Source image processing edge detection(Image processing edge detection source Source image processing edge detection)

truncated DCT. good for video compression.

Multi-Scale Structural Similarity Index (MS-SSIM). Download here. Please cite the following paper in any published work if you use this software. Z. Wang, E. P. Simoncelli and A. C. Bovik, "Multi-scale structural similarity for image quality assessment," IEEE Asilomar Conference Signals, Systems and Computers, Nov. 2003.

粒子滤波器源代码，有助于学习。附有图像序列。(Particle Filter source code, contribute to learning. With image sequences.)

将没有exif文件信息的裸RAW数据转换成YUV422格式的数据.(Exif file information will not be the bare RAW data into YUV422 format.)

这是网上较难得到的一份基于主曲线轮廓提取的算法和论文，大家可以试一下！(This is a package of the paper and source of principal curve! It deserves you to have a try!)

说明：  This is BM3D algorithm implemented according to the paper: K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3D transform-domain collaborative filtering,” IEEE Trans. Image Process., vol. 16, no. 8, pp. 2080-2095, August 2007.(This is BM3D algorithm implemented according to the paper: Image denoising by sparse 3D transform-domain collaborative filtering)