图像锐化算法，锐化的效果很明显，能达到预期的效果，很适合应用再实践中，运行速度一般。...

一篇关于医学图像分割方法的调查研究，该文章总结了常见的医学领域中的图像分割方法。-About a method of medical image segmentation research, the article summarizes the common in the field of medical image segmentation method.

/* This program is to read and write bmp images */ bit图的读写操作，很值得一看-/* This program is to read and write bmp imag es*/bit map reading and writing operations, is an eye-catcher

基于Hough变换的火柴根数检测--Matlab7.0.4上开发-Based on the Hough Transform Detect root number of matches- Matlab7 .0.4 developed

在matlab上实现一种经高斯平滑的边缘检测算法-In matlab by Gaussian to achieve a smooth edge detection algorithm

Matlab环境下的几个数字图像处理实验，包含图像灰度变换、直方图均衡化、直方图匹配、邻域平均、局域增强、中值滤波、图像的锐化等-Several digital image processing experiments, including gray transform, histogram equalization, histogram matching, neighborhood average, local increase, median filtering and image sharpening, etc.

图像余旋变换（Cosine Transformation）是一种频域变换，广泛应用于图像处理。本代码实现了图像Cos变换，非常经典，带图片可测试.-image rotation transform (Cosine Transformation) is a frequency-domain transform, widely used in image processing. Implementation of the code of the image Cos transform, very classic, with pictures can be tested.

一个图像处理软件,可以处理基本的图像哈，有兴趣的-An image-processing software, you can deal with the basic image of Kazakhstan, are interested in

图像增强，基于视网膜图片的图像增强，C++Builder环境下运行-Image enhancement, image enhancement based on the retinal image, C++ Builder environment running

：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出 应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音 乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高 斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪 方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the traditional de-noising method in case of strong background noise, the ability to extract the voice signal even weaker failure, the application of independent component analysis (ICA) method of voice signal feature extraction, and prove that this transformation can be enhanced voice ICA and music of super-Gaussian signals. On this basis, the application of ICA basis function as a filter, through the threshold of the denoising method of Gaussian background noise contains strong voice signal denoising simulation. The results show that this method is obviously superior to the traditional mean filtering and wavelet denoising methods for the strong background noise under the weak signal detection provides a new way.