matlab图像处理

图像420转换为422或444的算法。高斯加噪算法，脉冲加噪算法。(YCbCr 4:2:0 image is converted to 4:2:2 or 4:4:4 of the algorithm, Matlab program is)

超分辨率POCS（投影到凸集集合理论复原方法）算法代码(The POCS super-resolution algorithm code)

Matlab 实现的带阻滤波器设计。基于高斯带阻滤波器。实现冈萨雷斯《数字图像处理》第五章的实例。(Matlab implementation of the band stop filter design. Based on Gaussian band-stop filter. Achieve Gonzalez, " Digital Image Processing" Chapter V of the instance.)

迭代最佳阈值分割算法，寻找最佳阀值检测边缘(best iteration threshold segmentation algorithm to find the best edge detection threshold)

将RGB格式的图像转换为灰度模式。 使用TI C6748 DSP 在CCS5.5下运行(convert RGB image to grey code. use in C6748DSP. written under CCS5.5. )

2-band discrete wavelet transform (DWT) Dual-Tree Complex Wavelet Packet(The 2-band discrete wavelet transform (DWT) provides an octave-band analysis in the frequency domain, but this might not be ‘optimal’ for a given signal. The discrete wavelet packet transform (DWPT) provides a dictionary of bases over which one can search for an optimal representation (without constraining the analysis to an octave-band one) for the signal at hand. However, it is well known that both the DWT and the DWPT are shift-varying. Also, when these transforms are extended to 2-D and higher dimensions using tensor products, they do not provide a geometrically oriented analysis. The dual-tree complex wavelet transform (DT-CWT), introduced by Kingsbury, is approximately shift-invariant and provides directional analysis in 2-D and higher dimensions. In this paper, we propose a method to implement a dual-tree complex wavelet packet transform (DTCWPT), extending the DT-CWT as the DWPT extends the DWT. To find the best complex wavelet packet frame for a given signal, w)

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.)

利用全卷积神经网络，实现图像的语义分割，基于tensorflow的keras可以直接运行(Using the full convolutional neural network to achieve semantic segmentation of images, keras based on tensorflow can be run directly)

说明：  BMED二维经验模态分解，用于处理二维信号(Two dimensional empirical mode decomposition)

计算haar尺度函数和小波基系数矩阵，用于数值计算，如解偏微方方程，自己编写的。(Computing haar wavelet scaling function and the coefficient matrix for the numerical calculation, such as the solution of partial differential equations side, I have written.)