图像处理

CZT变换进行信号频谱分析，解决了FFT法频域分辨不高的问题，源码开发，特别适用(Chirp Z Transform)

Adaptive Perona–Malik Model Based on the Variable Exponent for Image DenoisingThis paper introduces a class of adaptivePerona–Malik (PM) diffusion, which combines the PM

自主选择性的查看一幅图像中的部分区域的颜色直方图：允许用户在一幅图像中选择一个矩形区域，通过按住鼠标键画一个矩形，当鼠标放开是，高亮显示矩形框，同时在另一个独立的窗口中，使用画图函数画一个图表（选定区域的颜色直方图），分别用蓝，绿，红表示选中区域中每种颜色的像素数量。(Self-selective color in an image to view a partial area of ​ ​ the histogram: Allows the user to select a rectangular area in an image by holding down the mouse button to draw a rectangle when the mouse is released, the highlighted rectangle, Meanwhile in a separate window, using the drawing functions to draw a chart (selected color histogram region), respectively, with blue, green, red indicates the number of pixels in the selected area of ​ ​ each color.)

实现DCT与DWT相结合的算法,用matable及小波变换实现所想构思。(The algorithm of combining DCT with DWT is realized, and the idea is realized by matable and wavelet transform.)

实现混合高斯的功能，再次基础上可进行任意操作(The function of mixed Gaussian can be realized, and any operation can be carried out on the basis of it again.)

实现了图像的加水印，去噪，加噪声等功能，基于kaiser窗的双谱线插值FFT谐波分析，用于建立主成分分析模型。( Realize image watermarking, de-noising, plus noise and other functions, Dual-line interpolation FFT harmonic analysis kaiser windows, Principal component analysis model for establishing.)

PCA（主成分分析法）和ICA（独立成分分析法）的MATLAB源程序，他们是目前图像处理比较经典的特征提取方法(PCA (Principal Component Analysis) and ICA (independent component analysis) of the MATLAB source code, they are comparing the current image processing feature extraction methods of classical)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)

本人开发的火焰识别程序，包括otsu自适应阈值，canny边缘检测，形态学膨胀、腐蚀操作，尖角判别，圆形度计算。在vc下编译通过。(development of the flame identification procedures, including otsu adaptive threshold, canny edge detection, Morphological expansion, corrosion operation, pointed discriminant, circular calculation. Under the vc compile.)

实现人脸识别功能，GUI界面，其中有测试人脸集，识别率95以上(To achieve face recognition function, GUI interface)