GIST_matlab

经典主成分分析法，实现高光谱图像的降维处理 (Classical principal component analysis, to achieve high spectral image dimensionality reduction)

基于DCT域的数字水印算法主要包括水印调制、水印嵌入和水印提取，首先在嵌入载体图像之前用Logistic混沌序列对水印进行调制，得到一个只有+1和-1随机序列的水印，同时将载体图像进行全局DCT变换，然后将水印图像嵌入人类视觉系统最重要的部分，即DCT最大的系数，DC（Direct Current）部分也包含在这最大的系数中，这部分的系数满足人类视觉特性，会使水印嵌入的性能更好。嵌入算法是将水印与这些系数进行相乘获得新的系数，再用新的系数来替换原来的系数，即获得嵌入水印后的离散余弦域的图像，然后对这个变换后的图像进行IDCT，就会得到需要的水印图像。(While the carrier image digital watermarking algorithm based on DCT domain include watermark modulation, watermark embedding and watermark extraction, the first of the watermark embedded in a carrier modulated image before using Logistic chaotic sequence, only+1 and-1 to get a random sequence of watermark, Global DCT transform, then the watermark image is embedded most important part of the human visual system, i.e. the largest DCT coefficients, DC (Direct Current) in this section also contains the largest coefficient, the coefficient of this part of the human visual characteristics to meet, make watermarks Embed better performance. The watermark embedding algorithm is with these coefficients are multiplied to obtain new coefficients, and then a new factor to replace the original coefficients, namely discrete cosine domain to obtain an image watermarked and then transformed the image of this conduct IDCT, on watermark image will be needed.)

包括一片英文文献及其所对应的代码实现，主要功能是实现对运动模糊图像的复原。(Including an English literature and its corresponding code, the main function is to achieve restoration of motion blurred images.)

说明：  生成显著图方法，一种基于空间频域分析的显著性分析算法（Spectral Residual，SR算法）的matlab实现代码(Matlab code generated saliency map method based on the spatial frequency domain analysis of significant analysis algorithm (Spectral Residual, SR algorithm))

基于matlab的ssim图像质量评价，验证还可以(Image quality evaluation)

解决一些图像处理的小问题，具体的划分和问题，文件里有提到(Solve some small problems in image processing)

利用matlab提取掌纹图像的感兴趣区域，ROI提取(Extract palmprint images using matlab region of interest, ROI extraction)

冲激函数、阶跃函数及三角函数的小波变换、模极大线并求它们的李氏指数(The impulse function, step function and wavelet transform of the trigonometric function, the modulus maxima line and the Lipschitz exponents)

figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds。 Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c. (figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds. Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c.)

用于图像处理上的相邻像素点之间相关性的计算，主要用于分析像素值之间的关联度(For the calculation of the correlation between the pixels on the image processing)