ellipse-detection-algorithm

新的水下图像对比度增强和分割算法（实现对比度的增强和图像分割，内容包括：新的水下图像对比度增强算法、水下图像的分割算法--2008a）(The new underwater image contrast enhancement and segmentation algorithm (implemented contrast enhancement and image segmentation, including: new underwater image contrast enhancement algorithms, underwater image segmentation algorithm- 2008a))

这是一个利用python里微信机器人，然后获取微信好友的照片，然后利用图像处理，把照片合成在一张照片里。(This is a use of the python Weixin robot, and then get the pictures of Weixin friends, and then use image processing to synthesize the pictures in a picture.)

说明：  图像分割的MATLAB实现，效果很好，对光照有一定的适应性(Image Segmentation of MATLAB to achieve good effect on the light a certain degree of adaptability)

这本书提供了充分的代表性逆合成孔径雷达（ISAR）成像，这是一种流行和重要的雷达信号处理工具。本书涵盖了所有可能的ISAR成像方面。这本书提供了一个介绍了专家组的逆问题和合成孔径雷达（SAR）提出的问题之前，信号处理技术和雷达基本相当。如高分辨率SAR的重要概念，脉冲压缩和图像形成连同相关的MATLAB代码。 ISAR成像的基本原理后，这本书提供了相关的MATLAB函数和代码成像ISAR成像的详细程序。 ISAR成像，多个成像技巧和微调，如零填充和窗口程序，以提高图像的质量也被提出。最后，逆合成孔径雷达图像中的各种实际应用，如成像天线平台散射的，是在单独的一章。所有这些算法，MATLAB代码和数字都包括在内。最后一章考虑了在ISAR成像的先进理念和发展趋势。(This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes. After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLA)

1．选择一幅图像，对该图像进行DCT块操作（将图像分成8×8小块，对每个小块进行DCT变换）。 2.利用屏蔽矩阵对DCT系数进行区域选择，然后进行逆变换（IDCT），合成原图像，计算合成图像的PSNR。 3.选择一小波函数，对一幅图像进行分解，显示各变换系数，观察其规律，并进行小波逆变换，合成原图像。 (1. Select an image, the image DCT block operations (the image is divided into 8 × 8 small pieces of each small piece for DCT transform). 2. The use of shielding on the DCT coefficient matrix of regional choices, and then inverse transform (IDCT), synthesis of the original image, calculating the synthetic image PSNR. 3. To select a wavelet function, decomposition of an image to show the transform coefficients, to observe its laws, and inverse wavelet transform, the original synthetic image.)

Real-time Specular Highlight Removal实现论文“Real-time Specular Highlight Removal Using Bilateral Filtering”中算法(Real-time Specular Highlight Removal Papers " Real-time Specular Highlight Removal Using Bilateral Filtering" in the algorithm)

说明：  一个纹理坐标自动生成的例子，有助于理解纹理坐标自动生成的各个函数(An example of automatically generated texture coordinates, texture coordinates generated automatically help you understand the various functions)

小波去噪算法，包含多种小波去噪去噪，强制去噪、软阈值去噪、硬阈值去噪(Wavelet denoising algorithm that contains a variety of wavelet denoising denoising forced denoising, soft thresholding and hard threshold denoising )

用模糊C均值算法实现图像分割 ，文件夹中附带有图片和matlab的源程序，已经验证过可以实现对图片的分割 (Fuzzy C-means algorithm for image segmentation, there is a folder with pictures and matlab source, has already been verified can be achieved on image segmentation)

智能算法实现图像分割，读取一张黑白图片进行阈值分割。(Intelligent algorithms for image segmentation, read a black and white image thresholding.)