Search Results for "image steganography code"
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Showing 23 open source projects for "image steganography code"
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Image Fusion
Deep Learning-based Image Fusion: A Survey
This repository is a survey / code collection centered on deep learning–based image fusion (e.g. fusing infrared + visible light images, multi-modal fusion) methods. It catalogs many fusion algorithms (e.g. DenseFuse, FusionGAN, NestFuse, etc.), links to code implementations, and describes evaluation metrics. The repository includes a “General Evaluation Metric” subfolder containing objective fusion metrics. -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
...Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition. -
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gptoolbox
Matlab toolbox for Geometry Processing
...It also implements discrete differential geometry operators, geodesic distance computations, and constructive solid geometry operations. Beyond geometry, gptoolbox includes features for quadratic programming, image colorization, and dithering. Most of the functions are pure MATLAB code, requiring only that the toolbox be added to the MATLAB path, while some specialized features depend on external libraries and compiled mex files. -
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ReViMS
ReViMS, a 3D volume rendering tool for light-sheet/confocal microscopy
...It provides a number of tools for: (a) segmenting z-stacks of fluorescence images; (b) reconstructing the 3D surface of the aggregates and estimating several features (including the volume). ReViMS is written in MATLAB (The MathWorks, Inc., Massachusetts, USA). It is an open-source tool and the source code is freely available at: http://sourceforge.net/p/revims Requirements: MATLAB R2017b and Image Processing Toolbox 10.1 or later versions. -
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Exposure Correction
Learning multi-scale deep model correcting over- and under- exposed
...This allows the model to preserve fine details while correcting global lighting inconsistencies. The repository includes pre-trained models, datasets, and training/testing code to enable reproducibility and experimentation. By leveraging this framework, researchers and developers can apply exposure correction to a wide range of natural images, improving visual quality without manual editing. The project serves both as a research reference and a practical tool for computational photography and image enhancement. -
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ReViSP
ReViSP, a 3D volume rendering MATLAB tool for multicellular spheroids
Reconstruction and Visualization from a Single Projection (ReViSP) tool: a 3D volume rendering method we developed to reconstruct the 3D shape of multicellular spheroids, besides estimating the volume by counting the voxels (3D pixels) fully included in the 3D surface. ReViSP is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code is freely provided. Requirements for running ReViSP from the source code: MATLAB 2020a and Image Processing Toolbox 11.1 or later versions. Please, when using this software, cite these articles: (a) F. Piccinini, et al., Cancer multicellular spheroids: Volume assessment from a single 2D projection. Computer Methods and Programs in Biomedicine, 118(2):95–106, 2015. ... -
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DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN
This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. ... -
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VRN
Code for "Large Pose 3D Face Reconstruction
The VRN (Volumetric Regression Network) repository implements the “Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression” method. Instead of explicitly fitting a 3D model via landmark estimation and deformation, VRN treats the reconstruction task as volumetric segmentation: it learns a CNN to regress a 3D volume aligned to the input image, and then extracts a mesh via isosurface from that volume. The network is unguided (no 2D landmarks as intermediate).... -
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CAM
Class Activation Mapping
...The repo provides example code and instructions for applying CAM to existing CNN architectures. Visualization of discriminative regions per class. -
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...The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. This resource serves as both an educational reference and a foundation for further exploration in image retrieval research.
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ANDTool
Analysis Nuclei DAB (AND) Tool
Analysis Nuclei DAB (AND) Tool is a Graphical User Interface (GUI) to analyse microscopy images representing cells with nuclei stained using DAB dyes. The tool requires as input the original RGB images, and the FastRed, FastBlue, DAB channel, easily obtained using the Fiji function: "ImageJ" -> "Image" -> "Colour Deconvolution" -> "FastRed FastBlue DAB" Then, the tool first segment the nuclei using the FastBlue channel and the DAB channel, and then computes statistics by subdividing the sample in three regions according to the FastRed channel: a dark-red ROI, a light-pink ROI and a white ROI. ANDTool is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code and standalone versions are here available for download. ... -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). ... -
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ConvNet Burden
Memory consumption and FLOP count estimates for convnets
convnet-burden is a MATLAB toolbox / script collection estimating computational cost (FLOPs) and memory consumption of various convolutional neural network architectures. It lets users compute approximate burdens (in FLOPs, memory) for standard image classification CNN models (e.g. ResNet, VGG) based on network definitions. The tool helps researchers compare the computational efficiency of architectures or quantify resource needs. Estimation of memory consumption (e.g. feature map sizes,... -
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Brain imaging software produced by the Brain Research Imaging Centre of The University of Edinburgh.
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HashingBaselineForImageRetrieval
Various hashing methods for image retrieval and serves as the baseline
This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets. -
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F-Tracker3D
A software tool for tracking fluorescent cells in 3D
...Then, the 3D track of each cell is obtained analysing the z-stacks and looking for the z-plane with the maximum intensity value for the different x-y positions previously determined. F-Tracker3D is written in MATLAB (©, The MathWorks, Inc., Massachusetts, USA) and the source code is freely provided. Requirements: MATLAB 2015a and Image Processing Toolbox 9.2 or later versions. -
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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IBEX_MDA
An open infrastructure software to facilitate radiomics research.
This web page is not guaranteed to have the latest versions. The latest stand-alone version can be downloaded at http://bit.ly/IBEX_MDAnderson The latest source-code version can be downloaded at http://bit.ly/IBEXSrc_MDAnderson IBEX (imaging biomarker explorer) is an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. ... -
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ApproxAdderLib
Library of Approximate Adders
We provide MATLAB and Verilog Models of GeAr, and previously proposed adders (ACA-I, ETAII, ACA-II and GDA) at http://sourceforge.net/projects/approxadderlib/ GeAr is a low latency Generic Accuracy Configurable Adder that provides a higher number of potential configurations compared to state-of-the-art approximate adders, thus enabling a high degree of flexibility and trade-off between performance and output quality. These MATALB and Verilog models can allow software programmer as well as hardware designers to evaluate their code and design. To the best of our knowledge, this is the first open-source library of approximate adders that facilitates reproducible comparisons and further research and development in this direction across various layers of design abstraction. This work is a result of collaborative effort between Chair for Embedded Systems (CES) at Karlsruhe Institute of Technology (KIT), Germany and Vision Image and Signal Processing (VISpro) Lab at SEECS-NUST, Pakistan. -
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LS-PIV Supplemental Material
Line-scanning particle image velocimetry for analyzing blood flow data
Line-scanning particle image velocimetry (LS-PIV) is an analytical method to quantify blood velocity data generated by many confocal and two-photon excited fluorescence microscopes. We hope that this method will be of use to the research community! The associated files include Matlab code for LS-PIV and example data-sets of measured blood flow in the cerebral cortex of mouse. -
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CIVx is a free advanced PIV (Particle Imaging Velocimetry) code, developped in Fortran and C++. Input : pair of png images. Output : velocity field in NetCDF format. It is used by the UVMAT Matlab code develloped at LEGI.
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A Matlab code to characterize and analyze Gafchromic film for radiotherapy applications. Single or dual color analysis (respectively for EBT or EBT2 film types). Accurate uncertainty estimations. Requirements: Matlab (min. ver. 2007a), Image toolbox.
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golib
C++ collection mostly for image processing
libGo is a C++ class library containing all kinds of things that proved useful to me. Included are: - Linear algebra, using LAPACK and CBLAS - V4L(1) image grabber - Multithreading - Image containers (up to 3D) - Some simple optimisation code - Python embedding helper - Matlab interface - .. and other things, have a look at the HTML documentation! golib grew over many years, things I had use for have been added now and then. Some parts are better taken care of than others. ...
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