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qiuleng_v51
- 包括面积、周长、矩形度、伸长度，用平面波展开法计算二维声子晶体带隙,在MATLAB中求图像纹理特征。- Including the area, perimeter, rectangular, elongation, Computation Method D phononic bandgap plane wave, In the MATLAB image texture feature.
entttos_mode
- 计算图像纹理共生矩阵及共生矩阵相关系数,熵等几个特征值,很好-Correlation coefficient calculation for image texture co-occurrence matrix and co-occurrence matrix, the entropy value, several characteristics, such as well
koukuisen
- 非归零型差分相位调制信号建模与仿真分析 ，计算目标和海洋回波的功率谱密度,在MATLAB中求图像纹理特征。- NRZ type differential phase modulation signal modeling and simulation analysis, Calculating a target and ocean echo power spectral density, In the MATLAB image texture feature.
sounan
- MIMO OFDM matlab仿真,有均匀线阵的CRB曲线，考虑雨衰 阴影 和多径影响，添加噪声处理，实现典型相关分析，针对EMD方法的不足,基于负熵最大的独立分量分析，在MATLAB中求图像纹理特征。 - MIMO OFDM matlab simulation, There ULA CRB curve, Consider shadow rain attenuation and multipath effects Add noise processing, Achieve canonica
Cloud-detection-
- 首先使用灰度共生矩阵提取图像纹理特征，之后使用灰度共生矩阵的熵值与相关性系数作为纹理参数，用k-means聚类算法实现遥感图像的云检测-First of all, the gray co-occurrence matrix is used to extract the image texture features, then the entropy and correlation coefficients of the GLCM are used as texture parameters, a
setay
- 数据模型归一化，模态振动，基于分段非线性权重值的Pso算法，在MATLAB中求图像纹理特征。- Normalized data model, modal vibration, Based on piecewise nonlinear weight value Pso algorithm, In the MATLAB image texture feature.
cy347
- GSM中GMSK调制信号的产生，在MATLAB中求图像纹理特征，滤波求和方式实现宽带波束形成。- GSM is GMSK modulation signal generation, In the MATLAB image texture feature, Filtering summation way broadband beamforming.
bunnui_v51
- 在MATLAB中求图像纹理特征，主要是基于mtlab的程序，使用混沌与分形分析的例程。- In the MATLAB image texture feature, Mainly based on the mtlab procedures, Use Chaos and fractal analysis routines.
np760
- music高阶谱分析算法，在MATLAB中求图像纹理特征，多元数据分析的主分量分析投影。- music higher order spectral analysis algorithm, In the MATLAB image texture feature, Principal component analysis of multivariate data analysis projection.
ac631
- 采用累计贡献率的方法，在MATLAB中求图像纹理特征，gmcalab 快速广义的形态分量分析。- The method of cumulative contribution rate In the MATLAB image texture feature, gmcalab fast generalized form component analysis.
pingkang_v74
- 在MATLAB中求图像纹理特征，用于信号特征提取、信号消噪，用蒙特卡洛模拟的方法计算美式期权的价格以及基本描述。- In the MATLAB image texture feature, For feature extraction, signal de-noising, Monte Carlo simulation method of calculating the American option price and basic descr iption.
bf433
- 在MATLAB中求图像纹理特征，基于matlab平台实现,数值分析的EULER法。- In the MATLAB image texture feature, Based on matlab platform, EULER numerical analysis method.
LBP代码
- 常用于计算机视觉领域，提取图像的纹理特征，用于人脸识别、掌纹识别等。(It is often used in the field of computer vision to extract the texture features of images, such as face recognition, palmprint recognition and so on.)
nsct_toolbox
- 非下采样contourlet是超小波的一种。具有多尺度和多方向性，解决了contourlet变换无平移不变性的缺陷。用于图纹理特征提取和图像融合的效果很好。(Non sampled contourlet is a kind of super wavelet. With multi-scale and multi directional, it solves the defect of Contourlet translation without translation invariance. F
sfta
- 根据图像的特征自动划分多个二值化阈值，对二值化阈值进行纹理分析，获得纹理的分维数，根据纹理识别对象。(According to the features of the image, two threshold values are automatically divided, and the texture of the two threshold is analyzed to obtain the fractal dimension of the texture, and the object
SRCNN_v1
- 主要用于图像增强，眼白血管纹理增强，运用的是深度学习算法，超分辨率(For image enhancement, white vascular texture enhancement is the use of deep learning algorithms, super-resolution)
SummerWork
- 基于内容的图像检索程序，使用颜色、纹理、形状特征实现对选定图片在图片集中的检索(Content based image retrieval program)
lbp500b可用
- 基于LBP纹理的图像检索，亲测可用，小白能看懂(LBP texture based image retrieval, pro test can be used, Xiao Bai can understand)
program
- 我们在这里将要介绍一种通用的灰度图像彩色化的技术，它可以将彩色源图像的彩色信息传 递给目标灰度图像。尽管将彩色信息传递给灰度图像没有一个准确、客观的解决方案，但是目前 流行的方法是尝试去将人的劳动量降到最低。与其从一个调色板选择RGB三彩色去给目标图像着 色，倒不如我们通过匹配图像之间的亮度和纹理来传递源图像的色度信息。我们仅仅传递源图像 的色度信息，而不改变目标图像的亮度值。此外，这种灰度图像彩色化技术的效果也通过允许用 户使用矩形表(swatches)来选择源图像和目标图像匹配区域
lena512color
- tiff格式的lena原图，该图像包含了各种细节、平滑区域、阴影和纹理，这些对测试各种图像处理算法很有用。(Lena artwork in TIFF format,The image contains a variety of detail, smooth areas, shadows, and textures, which are useful for testing various image processing algorithms.)