Search Results for "resolution"

This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful...

Application that paints a subtly colored ball over the images of a directorio, that you can browse. It has been an excuse for integrating the JColorChooser with my library: * Multi-precision * Dark mode * It remembers the latest chosen colors you can watch a demo...

Bring Your Old Photos to Life with RetroShine – Vibrant, Authentic, and Instantly Beautiful RetroShine transforms your digitized analog photos with a single click. Whether you’re reviving family memories or preserving your artistic legacy for future generations, RetroShine uses intelligent color enhancement and curve corrections to restore natural tones and give your photos a fresh, contemporary look. Authenticity is our mission. Unlike generative AI tools, RetroShine doesn’t...

...It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on images such as edge detection and color clustering have also been added. GIMP-ML relies on standard Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy. In addition, GIMP-ML also aims to bring the benefits of using deep learning networks used for computer vision tasks to routine image processing workflows.

TracTrac is a Particle Tracking Velocimetry (PTV) software which is extremely fast (more than 10k points tracked per second, 100k under python) and accurate (up to 0.01 pixel resolution), forming thus a good concurrent to the state-of-the art PIV/PTV algorithms. It allows to track anything that moves: birds, ants, grains, water flows... It runs on Python (v2&3) or Matlab (>2012a with Image Processing toolbox). Give it a try ! Get the last sources on GitHub: https://github.com/jorishey1234/tractrac

Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model. ACM Transactions on Graphics (presented at SIGGRAPH 2018) Exposure is originally designed for RAW photos, which assumes 12+ bit color depth and linear "RGB" color space (or whatever we get after demosaicing). jpg and png images typically have only 8-bit color depth (except 16-bit pngs) and the lack of information (dynamic range/activation resolution) may lead to suboptimal results such as posterization. ...

The TESTIMAGES archive is a huge and free collection of sample images designed for analysis and quality assessment of different kinds of displays and image processing techniques. The archive includes more than 2 million images originally acquired and divided in three different categories: SAMPLING and SAMPLING_PATTERNS (aimed at testing resampling algorithms), COLOR (aimed at testing color rendering on different displays) and PATTERNS (aimed at testing the rendering of standard geometrical...

The Orfeo Toolbox is a C++ library for high resolution remote sensing image processing. It is developped by CNES in the frame of the ORFEO program. More information is available at www.orfeo-toolbox.org It is based on the medical image processing library ITK and offers particular functionalities for remote sensing image processing in general and for high spatial resolution images in particular.