matlab

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

高斯平滑滤波实例，高斯滤波实质上是一种信号的滤波器，其用途是信号的平滑处理，我们知道数字图像用于后期应用，其噪声是最大的问题，，由于误差会累计传递等原因，很多图像处理教材会在很早的时候介绍Gauss滤波器，用于得到信噪比SNR较高的图像（反应真实信号）。 (Instance of the Gaussian smoothing filter, Gaussian filter is essentially a signal filter, its purpose is to smooth processing of the signal, we know that the digital image for the late application, the noise is the biggest problem, the error accumulated transfer reason, a lot of image processing textbooks will be introduced at an early Gauss filter for higher SNR of the image (real response signal).)

Canny边缘检测算法,canny算法计算梯度,并从小波模极大重构图像.(Canny edge detection algorithm, canny algorithm for calculating the gradient, and from the Wavelet Modulus Maxima Image Reconstruction.)

自己编写的一个MATLAB 的水平、垂直灰度投影，程序简单易懂，希望对大家有用。(I have written a MATLAB horizontal, vertical gray projection, the program easy to understand, want to be useful.)

SSDA序贯相似性检测方法对图像进行模板匹配。从源图像中取小图，再到源图像中找到小图所处的位置。(SSDA sequential similarity detection method of the image template matching. Source image taken from the small map, to find a small map the source image position.)

一种可适用于复杂光照环境的低照度图像增强算法，即基于内容感知的自适应对比度提高的增强算法。引入了改进的伽马矫正，可以根据低照度图像的明暗程度自适应的对图像进行预处理。在实验过程中还发现，虽然改进算法有效避免引入大量噪声，但仍有少量噪声存在，为了达到更好的视觉效果，利用改进的双边滤波对增强的图像进行处理，获得最后的增强图像。实验效果显示，该算法可对低照度图像实现理想的增强效果。(A can be applied to complex light environment of low illumination image enhancement algorithm, which based on the content of perception adaptive contrast enhancement algorithm. Introduced the improvement of gamma correction, can according to the low illumination image of light and shade degree adaptive to image preprocessing. In the process of experiment also found that although the improved algorithm effectively avoid introducing a lot of noise, but there still have a small amount of noise, in order to achieve better visual effect, use of improved bilateral filtering to enhance the image processing, finally enhance image. The experimental results showed that the algorithm can achieve a low illumination image enhancement effect. )

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

粒子滤波去噪 含噪情况下应用粒子滤波技术可以去除噪声(Particle filtering noise with noise case using particle filtering techniques can remove noise)

基于自适应技术的遗传算法matlab源码，可应用于图像的去噪处理(based on adaptive technology GA Matlab source can be applied to the image denoising)

说明：  MTLAB编写的程序，包括形态学梯度检测二值图像的边缘、用水线阈值法分割图像等。(MTLAB preparation procedures, including detection of morphological gradient binary image of the edge of the water line thresholding segmentation images.)