使用purebasic开发的图像边缘检测的源代码，并附上了原始和检测后的图像。...

小波分析理论入门，对图像处理信号分析的研究人员很有意义，强烈推荐-Introduction to the theory of wavelet analysis, signal analysis of the image processing researchers meaningful strongly recommend

bmp文件读取，写入库程序。可读取/写入bmp格式及ico格式文件，为后续图象处理所用-bmp file to read, write, warehousing procedures. Can read/write format bmp and ico format for follow-up image processing by

：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.

图像处理源程序代码，关于图像的梯度锐化处理。-Image processing source code, the gradient sharpening on the image treatment.

VC 6 VC.net 2003 VC.net2005下可以编译通过。 用于位置的变换的类-VC 6 VC.net 2003 VC.net2005 under compile. For the location of the type of transformation

这是一个图像融合程序，在VC下编写的，很有使用价值-This is an image fusion procedure, in the VC prepared, very useful

sift算法的c算法，基于opencv的，一个大牛写得，很厉害的。-c algorithms sift algorithm, based on the opencv, a large cattle write, it is powerful.

别人的东西，有关KPCA特征提取的，看过了，很好很强大-Other people" s things, the KPCA feature extraction, and seen, very good very strong

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这是类似photoshop的灰度图算法。经计算很接近photoshop。可以用于很多图像处理算法。-This is similar to the grayscale algorithm photoshop. Calculated is very close to photoshop. Can be used in many image processing algorithms.