JSteg

说明：  一系列处理图片算法，简单的图片放大，打开时请打开project902.dsw，直接编译请重新下载(A series of image processing algorithms, simple image enlargement)

背景差分法，用于视频，该程序可直接运行。(Background differential method, used in video, can run directly.)

说明：  用来对数字全息图进行自动对焦，找到逼近真实焦距的焦距值来进行重建(a kind of criterion for automatic refocusing in DH)

对全息图进行卷积法的再现，利用matlab计算全息图模拟仿真(Reappearance of convolution method for hologram)

这是一个可以计算图片分形维数的软件，可用于图片分形维数计算(Fractal dimension of a picture can be calculated a small software)

说明：  基于信息熵进行图像质量评价，评价图像质量好坏。流程简单易于操作(Image quality evaluation based on information entropy)

说明：  这篇论文提出了一种较好的水下图像增强的方法。首先使用经过端到端训练的卷积神经网络去测量输入图片，同时以自适应双边滤波器对传输图片进行处理。接着提出一种基于白平衡的策略来消除图片的颜色偏差，用拉普拉斯金字塔融合获得无雾和色彩校正图像的融合结果。 最后，输出图像被转换为混合小波和方向滤波器组（HWD）域，用于去噪和边缘增强。 实验结果表明，该方法可以消除颜色失真，提高水下图像的清晰度。(This paper proposes a better underwater image enhancement method. Firstly, an end-to-end training convolutional neural network is used to measure the input image, and an adaptive bilateral filter is used to process the transmitted image. Then a strategy based on white balance is proposed to eliminate the color deviation of images. The fusion results of fog-free and color correction images are obtained by Laplacian pyramid fusion. Finally, the output image is converted into hybrid wavelet and directional filter bank (HWD) domain for denoising and edge enhancement. The experimental results show that the method can eliminate color distortion and improve the clarity of underwater images.)

计算特征的汉明距离作为特征匹配相似度的评价标准(The Hamming distance of the feature is used as the evaluation criterion of feature matching similarity)

说明：  IDL读取txt，txt第一列是纬度，第二列是经度，第三列是DN值， 坐标转行列号 ，并以图像的形式输出(IDL reads TXT. The first column of TXT is latitude, the second column is longitude, and the third column is DN value. The coordinate turns the line and column number and outputs it in the form of image)

自己实现的BM3D图像去噪算法。它首先把图像分成一定大小的块，根据图像块之间的相似性，把具有相似结构的二维图像块组合在一起形成三维数组，然后用联合滤波的方法对这些三维数组进行处理，最后，通过逆变换，把处理后的结果返回到原图像中，从而得到去噪后的图像。(Image Denosing by Sparse 3-D Transform-Domain Collaborative Filtering.)