A MATLAB/Octave toolbox for processing High Dynamic Range (HDR) images, including tone mapping and expansion operators.
HDR Toolbox is a MATLAB/Octave toolbox for processing High Dynamic Range (HDR) images. It provides algorithms for tone mapping HDR content to standard dynamic range, expanding low dynamic range images to HDR, and handling HDR image I/O operations. The toolbox solves the problem of manipulating and analyzing HDR data in research and development environments.
Researchers, academics, and developers working in computer vision, graphics, or imaging who need to process HDR content using MATLAB or Octave. It is particularly useful for those conducting scientific studies or developing algorithms related to high dynamic range imaging.
Developers choose HDR Toolbox because it offers a comprehensive, free, and well-documented set of HDR processing algorithms specifically for MATLAB/Octave. Its strong academic foundation and emphasis on proper citation make it a trusted resource for reproducible research in the HDR community.
HDR Toolbox for processing High Dynamic Range (HDR) images into MATLAB and Octave
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Includes a wide range of tone mapping and expansion operators, enabling advanced HDR processing as detailed in the features list, such as bilateral filtering and CRF handling.
Strongly emphasizes proper citation by referencing the author's book, supporting reproducible research and ethical use, as highlighted in the README's reference section.
Supports reading and writing .exr files through compiled C++ components, facilitating HDR image I/O operations for research workflows.
Provides functions for linearizing images by removing gamma encoding or CRF, which is mandatory for accurate processing with expansion operators, as noted in the README.
Some functionalities like .exr I/O and bilateral filtering require a C++ compiler and MATLAB MEX setup, adding complexity to installation and limiting portability.
The toolbox is exclusively for MATLAB and Octave, restricting use in other programming ecosystems like Python or C++, which may offer more modern alternatives.
Last updated in 2018, which means it may lack support for newer HDR standards, have unpatched bugs, or not integrate with recent MATLAB/Octave versions.
No mention of GPU acceleration or optimized performance for large datasets, potentially making it slow for intensive image processing tasks compared to specialized libraries.