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cuda_demosaicing

Demosaics RAW images on the GPU. This is the source code for the Cambridge MPhil project: https://www.dar.cam.ac.uk/drupal7/sites/default/files/Documents/publications/dcrr011.pdf.

Demosaicing is the process of converting raw sensor data into an RGB image. Sensors only collect only a single color at each pixel point, so the other RGB values have to be interpolated. However, this can lead to artefacts in the final image, in particular zippering on high contrast edges. More complex methods have emerged to prevent artefacts, the best being Adapative Homegenity Directed Demosaicing. But due to the complexity of the algorithm and the size of the images involved, demosaicing can be time consuming. This project is an investigation into how the GPU can be used to make this faster.

This project supports several demosaicing algoritihms including: Adapative Homegenity Directed Demosaicing, the algorithm with the highest quality results; Bilinear Interpolation, a fast and simple method; Edge Directed Demoasicing, a novel method of fast demosaicing that uses both AHD and Bilinear, using the more expensive method only on areas of the image where artefacts are likely to occur.

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cuda_demosaicing's Issues

Building with CUDA 9, 10...

Hi there,

Does anyone know how to remove old CUDA code (like cuda utilities) that was removed in CUDA 5 and later CUDA SDKs?

As far as I can tell a hack or work-around might be removing the cuda utils code and creating a new header, just cuda_utils.h, to resolve unknown functions and types, and making everything expecting the utils include that.

Then converting raw image files to PPM somehow: how did you achieve this in testing? I have tried raw2ppm but it throws an I/O error. I have raw files extracted from a Norpix seq file, and need to convert these to PPM to try some multi GPU demosaicing.

Trying to get this compiling and working using CUDA Toolkit 10.2. I'm using Ubuntu 18.04 LTS and Win 10. Thanks for any tips or ideas on getting this code running again!

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