jingdianEZW

256色显示文件。在DOS环境下用256原色显示BMP格式的图片。(256-color display documents. In the DOS environment display with 256 color BMP format picture.)

说明：  基于DSP和FPGA芯片的实时图像处理系统。该系统不同于传统基于PC机模式的图像处理系统，发挥了DSP和FPGA两者的优势，能更好地提高图像处理系统实时性能，同时也最 大可能地降低成本。(Real time image processing system based on DSP and FPGA. This system is different from the traditional image processing system based on PC mode. It can improve the real-time performance of the image processing system better by using the advantages of DSP and FPGAIt is possible to reduce costs.)

超像素线性分割聚类代码，可以运行，效果比较好，欢迎下载参考(SLIC code)

说明：  该算法实现了数字水印的嵌入与提取，然后对图像进行均衡化处理，分析均衡化处理后的图像对数字水印嵌入和提取效果的影响。(The algorithm realizes the embedding and extraction of digital watermark, and then carries on the equalization processing to the image, analyzes the influence of the equalization processed image on the embedding and extraction effect of digital watermark.)

通过小波阈值去噪，选取db5小波进行6层分解，对心音信号进行去噪(By wavelet thresholding, select db5 wavelet decomposition of six layers of the heart sound signal de-noising)

基于二维直方图最大熵阈值法的图像分割算法，可选取较好的阈值实现图像分割(failed to translate)

说明：  用matlab语言实现的图像平滑算法，效果较好，可设置不同的参数得到不同的平滑效果(Matlab language used to achieve the image smoothing algorithm, the effect is better, you can set different parameters of the smoothing effect of different)

线性反投影算法（Linear Back Projection，简称 LBP）又称累加法，是最早使用的一种简单（ECT图像重建）成像算法。它将通过某点的所有投影射线进行累加，再反向估算出该点的密度值。从成像观点分析，它是不完全的雷登逆变换（完整的雷登逆变换包括微分、希尔伯特变换、反投影和归一化等步骤）。(Linear back projection algorithm (Linear Back Projection, referred LBP), also known as cumulative method, is the first to use a simple (ECT image reconstruction) imaging algorithms. It accumulates all projection rays through a point, then reverse the estimated density value of the point. From the image point of view analysis, it is not exactly the inverse transform Leiden (Leyden complete inverse transformation involving differential Hilbert transform backprojection and normalization steps, etc.).)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

视频分割的matlab 程序,是用matlab开发的一个视频分割程序(Matlab video segmentation procedures are developed using matlab a video segmentation process)