Ggboy5656's Stars
MaheswaraReddy12/NSCT-IMAGE-FUSION
NSCT Image fusion
wliusjtu/Generalized-Smoothing-Framework
This is the released code for the following papers: A generalized framework for edge-preserving and structure-preserving image smoothing. Liu W, et al., TPAMI 2021, AAAI 2020
altlp/SKWGIF
YuanhaoGong/SideWindowFilter
Side window is better than Full window
weimin581/WSGGF
[PR'2024] ''Weighted side-window based gradient guided image filtering'', Weimin Yuan, Cai Meng, Xiangzhi Bai
oguzhankirlar/Convolution-filter-and-Object-Detection
Use convolution filtering on images and Object detection and replacement
Luxiush/Weighted-Guided-Image-Filter
TLiu2832/FAKPCoF
The MATLAB codes of Patch-based Co-occurrence Filter with Fast Adaptive Kernel (FAKPCoF)
sohaibali01/CGIF
Code for our paper "Contrast Aware Guided Image Filter"
UJS-112lab/Bilateral-Weighted-Guided-Image-Filtering
Bilateral Weighted Guided Image Filtering implemented by Yunch.
viengiaan/MGF_dehazing
Real-time image and video dehazing based on multiscale guided filtering, MTAP2022
Reanon/Homomorphic_Filtering
医学图像增强,使用同态滤波的方法
jiaxhsust/Significantly-Fast-and-Robust-FCM-Based-on-Morphological-Reconstruction-and-Membership-Filtering
A fast and robust fuzzy c-means clustering algorithms, namely FRFCM, is proposed. The FRFCM is able to segment grayscale and color images and provides excellent segmentation results.
souticksaha21/Biased-Persistence-Random-Walk-Model
This folder consists of codes written to explain cancer cell migration using Biased Persistence random walk (BPRW) for our paper : https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006961
yuanyc06/rcrr
Source code of the paper "Reversion correction and regularized random walks ranking for saliency detection"
xingpingdong/subRW
SubMarkov Random Walk for Image Segmentation, IEEE TIP 2016
JinleiMa/Multi-focus-Image-Fusion-with-Multi-scale-Focus-Measures
Multi-focus Image Fusion based on Multi-scale Focus Measures and Generalized Random Walk
Lihui-Chen/RGF_MDFB
Image fusion with rolling guided filter and multi-directional filter banks.
ChingCheTu/A-Multi-level-Optimal-Fusion-Algorithm-for-Infrared-and-Visible-Image
A Multi-level Optimal Fusion Algorithm for Infrared and Visible Image
congwang0705/Kullback-Leibler-divergence-based-Fuzzy-C-Means-algorithm-for-image-segmentation-IEEE-T-CYB-2022-
We elaborate on a Kullback-Leibler divergence-based Fuzzy C-Means (KLDFCM) algorithm by incorporating a tight wavelet frame transform and morphological reconstruction.
ixilai/CBFM
Code for CBFM: Contrast Balance Infrared and Visible Image Fusion Based on Contrast-Preserving Guided Filter (Remote Sensing 2023)
XHU-GMC/DTNP-IVIF
VCMHE/VE-HMD-Fusion
If you use this code, please refer to our following paper : Yueying Luo, Kangjian He, Dan Xu, Wenxia Yin, Wenbo Liu, “Infrared and visible image fusion based on visibility enhancement and hybrid multiscale decomposition”, Optik 258 (2022): 168914.
jianlihua123/ImageFusion_RGFF
Multi-scale image fusion through rolling guidance filter (FGCS2018).
hrtavakoli/FES
Code for Fast and efficient saliency detection using sparse sampling and kernel density estimation
Ghorbanpoor/Improved-segmented-image-with-PCNN-and-GA-in-Matlab
First, the image is segmented with PCNN and weights are obtained for the desired segment with the genetic algorithm of the two objectives to optimize the PSNR and MSE of the obtained image. The two-objective genetic algorithm program was taken from the aa site and we put our own program inside it.
Chinmaya-Panigrahy/MRI-and-SPECT-Image-Fusion-Using-a-Weighted-Parameter-Adaptive-Dual-Channel-PCNN
123former/A-Simple-PCNN-Model-with-the-Actual-Physical-Meanings-of-the-Parameters-for-Image-Segmentation
A Simple PCNN Model with the Actual Physical Meanings of the Parameters for Image Segmentation
wliusjtu/Embedding-Bilateral-Filter-in-Least-Squares-for-Efficient-Edge-preserving-Image-Smoothing
This is the released code for the following paper: "Embedding bilateral filter in least squares for efficient edge-preserving image smoothing." by Wei Liu, Pingping Zhang, Xiaogang Chen, Chunhua Shen, Xiaolin Huang, Jie Yang, IEEE Transactions on Circuits and Systems for Video Technology (2018).
VCMHE/IRfusion
If this work is helpful to you, please cite our paper: Wenxia Yin, Kangjian He, Dan Xu, et al., “Adaptive enhanced infrared and visible image fusion using hybrid decomposition and coupled dictionary. Neural Computing and Applications (2022). https://doi.org/10.1007/s00521-022-07559-w.