PHD_single_MM

说明：  1.学习使用fft2,ifft2,fftshift,ifftshift函数。用fft2函数对”lena.bmp”做二维傅立叶变换，并显示其频谱，用fftshift函数将频谱坐标原点移动到图像中心。用ifft2函数做傅立叶反变换。（提示：显示频谱时，可以先对频谱取对数，这样可以压缩动态范围很大的频谱，获得更好的显示效果）(1. Learn to use fft2, ifft2, fftshift, ifftshift functions. With the FFT 2 function, the lena.bmp'The two-dimensional Fourier transform is performed and the spectrum is displayed. The origin of the spectrum coordinate is moved to the center of the image by using the FFT shift function. The inverse Fourier transform is done with ifft2 function. (Note: when displaying the spectrum, the logarithm of the spectrum can be taken first, so that the spectrum with a large dynamic range can be compressed to obtain better display effect.))

求取相机响应函数，并绘制相对曝光量-灰度曲线(Camera response function, and draw the relative exposure- gray curve )

Region Based Active Contour Segmentation：基于活动轮廓的图像分割算法，ＭＡＴＬＡＢ代码，可用于目标提取，包括实验图片(Region Based Active Contour Segmentation: Active Contour-based image segmentation algorithm, MATLAB code, and can be used for object extraction, including the experimental image)

说明：  性能上比经典分水岭有很大的提高。特别对于自然图像的分割，效果特别好。(Performance than the classical watershed have greatly improved. Especially for natural image segmentation, the effect particularly good.)

说明：  图像处理案例，本程序是用matlab基于形态学的权重完成自适应图像去噪功能(Image processing case, this program is based on the weight of MATLAB morphology to complete adaptive image denoising function.)

对立体视觉的双目图像进行极线校正，以实现双目致密匹配(Of three-dimensional visual image of the binocular epipolar rectification to realize dense binocular matching)

人体脑图像分割技术研究a. 对原始的二维医学图像进行滤波，封装成三维体数据。 b. 采用合适的多阈值分割方法得到合适的双阈值，对三维体数据进行二值处理，得到分割出的三维人脑图像。 c. 对得到的三维人脑二值图像进行数学形态学操作，并利用种子填充进行区域修整，得到较好的三维人脑分割结果，并给以三维显示。 (err)

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

sample illust back image2 mask sample

RS攻击M程序,用于检测图像是否经过LSB密写(RS attack M procedures for detecting whether the image after LSB steganalysis)