搜索资源列表
Java图像处理
- 用Java实现的图像教学程序,涵盖大部分基本图像处理技术:(1)图像几何变换(图像翻转、旋转、缩放);(2)色彩变换(灰度直方图,RGB->YSH变换,对比度调整,色彩增强,灰度均衡);(3)卷积(锐化、柔化、边缘提取、中值滤波);(4)频率变换(快速傅立叶fft,小波分解重构)-A teaching program which implements in Java. It includes most essential image processing technology. 1.
WHJ
- 彩色图像处理包括彩色图像变换、彩色图像卷积滤波-color image processing, including color image transform, convolution filter color image
ImageConvolution
- 这是一个图像卷积运算的程序,功能做得非常好,而且效率非常之高,下了用了就知道
feature
- 图象经过gabor小波滤波。gabor小波与图像卷积。
Image-Enhancement-Using-Deconvolution-master
- 图像退卷积的几种方法,直接输入图片就能够进行相应的退卷积运算(Image deconvolution of several methods, directly enter the picture will be able to carry out the corresponding deconvolution)
DSP2017.6.8
- .通过图像与 sobel 算子的二维卷积,获得 lenna.tif 和 car.jpg 水平和垂直方向边缘。 2.通过图像与 Prewitt 算子的二维卷积,获得 lenna.tif 和 car.jpg 水平和垂直方向边缘。 3.进一步处理图像,定位出车牌位置。 二(License plate recognition after two-dimensional convolution removal)
cnn-示例
- 卷积神经网络的结构模型,可实现对图像进行训练与识别(The structure model of the convolution neural network can realize the training and recognition of the image)
Three_convolution
- matlab实现对图像的双三次卷积内插,以图像的缩放为例子(Matlab to the image of the double triple convolution interpolation, with the image zooming as an example)
CubicConvolution
- 采用三次卷积法对图像进行插值,进行n倍的缩放,有示例图片,有注释,可运行,欢迎交流。(Using the Cubic Convolution method for image interpolation, n times zoom, there are examples of pictures, notes, can run, welcome exchanges.)
FeatureExtractionUsingAlexNetExample
- 本示例展示了怎样从一个预处理的卷积神经网络中提取特征,并用这些特征去训练一个图像分类器。(This example shows how to extract learned features from a pretrained convolutional neural network, and use those features to train an image classifier. Feature extraction is the easiest and fastest way use
caffe
- 卷积神经网络的一种开源代码,可以对图像数据库自动提取特征(An open source code of the convolution neural network that automatically extracts features of an image database. (one open source code of CNN which can extract features other image dataset.))
cnn
- 基于python tensorflow框架构建的卷积神经网络用来识别图像,附带训练数据集的制作代码。(The convolution neural network based on the python tensorflow framework is used to identify images with the production code of the training data set.)
SRCNN_TEST
- 基于卷积神经网络的图像超分辨率重建,不含训练程序,包含已训练好的model !(Test code for Super-Resolution Convolutional Neural Networks (SRCNN))
matlab-blinddeconv
- 盲去卷积,实现图像的高分辨 准确估计模糊核(a novel scale-invariant regularizer that compensates for the attenuation of high frequencies and therefore greatly stabilizes the kernel estimation process.)
matlab程序
- 全变分去卷积算法的matlab实现; 全变分算法的论文; 全变分实现超分辨;全变分实现图像去噪;全变分实现图像恢复(total variation deconvolution; the paper of TV; super resolution; denoising; image recover)
cdbn_matlab-master(3)
- 卷积深度信念网络进行图像建模、分类等应用代码(Convolution depth belief network for image modeling, classification and other application code.)
adaptive TVMM demo
- 全变分图像反卷积:MAJORIZATION-MINIMIZATION方法。 《TOTAL VARIATION-BASED IMAGE DECONVOLUTION: A MAJORIZATION-MINIMIZATION APPROACH》这篇论文的源码 本文提出了一种新的在全变差正则化条件下图像反褶积的最大化-最小化算法。(Totally variational image deconvolution: The source of this paper TOTAL VARIATION-B
DnCNN-master
- 卷积神经网络进行图像去噪,比较经典的一篇文章代码。(The convolutional neural network performs image denoising and compares the classic article code.)
水下图像去雾与增强
- 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
cnn-edge-detection
- 卷积神经网络实现图像的边缘检测+python代码(CNN-edge-detection-python-codes)