TP2

L0梯度最小化算法，2011年由xuli提出的算法(L0 gradient minimization algorithm, in 2011 xuli put forward the algorithm )

基于FFT的配准程序，用在图像配准中的粗匹配中，对噪声、图像中物体发生运动等极为鲁棒！ (FFT-based registration procedure, used in image registration in the coarse matching, noise, motion and other image objects occur very robust!)

数字图像处理第三版(冈萨雷斯)附带课件PPT，第七章，英文原版(Digital Image Processing PPT by Gonzalez & Woods(3rd edition)，Chapter 7)

说明：  这是“An efficientlocalChan–Vesemodelforimagesegmentation”（简称LCV模型）的MATLAB源代码。LCV模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。(This is "An efficientlocalChan-Vesemodelforimagesegmentation" (referred to as the LCV model) of the MATLAB source code. LCV model is very important to local area active contour model, which is widely used in various fields, such as MRI brain image segmentation, vessel segmentation, image bias field correction.)

语音增强算法，谱减法、小波变换以及数学形态学等的语音增强算法针对信噪比、语谱图、去噪情况，分析比较(Speech enhancement algorithm, spectral subtraction, wavelet transform and mathematical morphology speech enhancement algorithm for signal-to-noise ratio, the spectrogram denoising situation analysis)

说明：  基于双边滤波的retinex算法，暗光图像增强，有效去噪、提高对比度、去光晕；含论文和讲解PPT、实例代码(Retinex algorithm based on bilateral filtering can enhance dark image, effectively denoise, improve contrast and eliminate halo)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

Image corrosion, swelling, binarization processing, image binary segmentation procedure matlab gui

通过用户给定的标签信息，来提取图像中的标记像素点位置，保存为种子点(Through the label information given by the user, the position of the label pixels in the image is extracted and saved as seed points.)

自相似特征（self-similarity）描述子的提取代码，算法见“Matching Local Self-Similarities across Images and Videos”(Self-similar characteristics (self-similarity) describe the extraction of sub-code, algorithms, see " Matching Local Self-Similarities across Images and Videos" )