搜索资源列表
2004w26-sourcecode
- 超分辨率图像重建。具有非常好的效果，程序效率较高，有完整的注释和说明文档。-super-resolution image reconstruction. Very good results, the higher the efficiency, integrity of the Notes and documentation.
openSNR
- 一种超分辨率处理测试程序。用于测试超分辨率算法的效率。打开一幅图像，选择降质，之后清晰的图像会变为多幅模糊图像。选择算法重建后模糊图像会经过处理变清晰。与原始图像比较后的效能参数将显示在右边。
Observation
- 超分辨率图像重建c++版，需要配置opencv-This is an implementation of the example-based super-resolution algorithm International Journal of Computer Vision
pocs
- 基于双边滤波的POCS超分辨率图像序列重建算法.-Bilateral filtering-based POCS super-resolution image sequence reconstruction algorithm.
SR-CODE
- 超分辨率图像重建matlab 源码，实现了超分辨率图像重建算法-super-resolution image reconstruction
Fast-and-robust-multiframesR
- 快速及鲁棒的超分辨率图像重建，利用盲解卷积的方法实现-Fast and robust super-resolution image reconstruction, the use of blind deconvolution method
Super-resolution-processing-
- 在重建超分辨率图像后会产生振铃现象，此论文用于优化Pocs方法-Maximum a posteriori and maximum likelihood estimation method of comparison, comparing their respective advantages
l2lap
- 采用L2范数的超分辨率图像重建,和拉普拉斯结合用！-super resolution reconstruction algorithm
image-mosaic
- 图像拼接技术可广泛应用于诸多领域，在宇宙空间探测、海底勘测、医学、气象、地质勘测、军事、视频压缩和传输、档案的数字化保存、视频的索引和检索、物体的三维重建、数码相机的超分辨率处理等领域都有广泛应用。 -Image stitching technology can be widely used in many fields, detection in space, seabed survey, medical, meteorological, geological surveying, mil
Keren---image-reconstruction
- 基于Keren配准和插值的快速超分辨率图像重建，具有很好的参考和科研意义-Keren registration and interpolation based on the rapid super resolution image reconstruction, has the very good reference and research significance
BIQI_release
- 用于对超分辨率重建后的重建影像进行无参考影像质量评价(the code is used for image quality measure without reference images)
Dual_Dic_SR
- 通过进行双字典学习来完成单幅影像超分辨率重建(use dual dictionary learning to single image super resolution)
icip10_deblur--new
- 利用字典学习去模糊的算法SINGLE IMAGE DEBLURRING WITH ADAPTIVE DICTIONARY LEARNING(SINGLE IMAGE DEBLURRING WITH ADAPTIVE DICTIONARY LEARNING)
SRCNN
- 是《Learning a Deep Convolutional Network for Image Super-Resolution》文章相关的MATLAB代码，可以利用训练好的字典，通过CNN实现超分辨率重建(SR)的功能。(Matlab demo code for "Learning a Deep Convolutional Network for Image Super-Resolution" (ECCV 2014) and "Image Super-Reso
新建文件夹
- 基于视频的超分辨率重建是指从许多帧连续的低分辨率图像中重建出一幅高分辨率的图像，并且这幅高分辨率的图像能够显示出单帧低分辨率图像中丢掉的细节(Super-resolution reconstruction based on video refers to the reconstruction of a high resolution image from a number of consecutive low resolution images, and this high resolution
SRCNN-Tensorflow-master
- 超分辨率重建 TensorFlow 实现 基于卷积网络(super resolution based on convolution network using tensorflow framework)
新建文件夹
- 实现基于卷积神经网络的图像超分辨率重建，并给出了PSNR值和SSIM值。(Realization of image superresolution reconstruction based on convolution neural network.)
ScSR
- 杨建超的将稀疏表达用于图像超分辨率重建的文章赋代码(Example matlab code for the algorithm proposed in "Image super-resolution via sparse representation" TIP 2010.)
超分辨率
- 第一层CNN：对输入图片的特征提取。（9 x 9 x 64卷积核） 第二层CNN：对第一层提取的特征的非线性映射（1 x 1 x 32卷积核） 第三层CNN：对映射后的特征进行重建，生成高分辨率图像（5 x 5 x 1卷积核）。