image-enhancement

LBP（局部二值模式）特征提取，用于人脸识别，(LBP feature extraction for face recognition. . .)

Gabor 小波变换用于面部表情特征提取(Gabor Transform用于表情识别)

利用霍夫变换进行直线检测的算法实现 设置不同的阈值来控制直线的输出(detect lines in image)

深度图像处理,主要的是对深度图像进行区域分割(depth map)

说明：  基于MATLAB，对逐日的sst遥感数据做月平均并制作gif动图(Based on MATLAB, the daily SST remote sensing data are averaged monthly and the GIF map is made)

传统的图像分割方法可以分为基于阈值、边缘、区域的方法等，而传统的分割方法在复杂图像分割中效果不好。为了提高图像分割的性能，我们提出了一种基于局部自适应窗口的Otsu方法。首先，分析了传统阈值法在复杂图像分割中不能很好地形成的原因，比较了全局阈值和局部阈值对图像分割的影响。其次，提出了根据局部信息自适应地改变局部窗口大小的方法，分析了该方法的特点。最后，证明了所提出的新方法优于其他方法。实验结果表明，与其他传统方法相比，该方法能保持更多的细节，获得更满意的结果。(The traditional image segmentation methods can be divided into thresholding, edge and region methods. The traditional segmentation methods do not perform well in the segmentation of complicated images. In order to improve the performance of image segmentation, we propose an adaptive windowed range-constrained Otsu method based on local information.First, the reason why traditional thresholding methods do not perform well in the segmentation of complicated images is analyzed. Therein, the influences of global and local thresholdings on the image segmentation are compared. Secondly, a method of adaptively changing the local window size based on local information is proposed, and the characteristics of the proposed method are analyzed. Finally, the superiority of the proposed method over other methods, It is validated by the experiments that the proposed method can keep more details and acquire much more satisfying results as compared with the other conventional methods.)

分别利用均值滤波、自适应滤波和中值滤波对噪声图像g1和g2进行滤波，利用峰值信噪比对去噪性能进行比较。(Respectively, using the mean filter, adaptive filtering and median filtering images g1 and g2 noise filtering, denoising performance comparison using the peak signal-to-noise ratio.)

IDL中用于读取ENVI格式的遥感卫星影像数据的IDL程序(IDL, ENVI format for reading remote sensing image data on the IDL)

改进型自适应陷波谐波检测法的研究，提高陷波器滤波功能(Improved Adaptive Notch harmonic detection method)

对两幅遥感图像进行变化监测，先求得差值图像，然后用FCM聚类方法分成变化类和不变类(On two remote sensing image change detection, the first difference image is obtained, then FCM clustering into the same category and class changes)