How to import Magic Lantern MLV clips to Adobe Premiere Pro CCMagic Lantern MLV RAW

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Digital cameras from Canon with Magic Lantern firmware are very popular. Nevertheless, there is no direct way to import MLV raw data into Adobe Premiere Pro CC. Usually it can be done via MLVFS (ML virtual file system) or via transform to CinemaDNG/DNG with mlv_dump utility. MLV raw format is open and raw data is stored either in incompressed 14-bit format or in compressed with Lossless JPEG encoding.

Currently, Adobe Premiere Pro CC software doesn't support MLV raw files, so it's impossible to import and to edit in Adobe Premiere Pro raw mlv files from Canon cameras with ML firmware. That's why the main idea to offer such a possibility is to implement MLV RAW converter to the format which is native to Adobe Premiere Pro CC. It means that transform from Magic Lantern MLV to CinemaDNG with Lossless JPEG compression or to Uncompressed CinemaDNG could be a solution for such a task.

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MLV pipeline at Fast CinemaDNG Processor

How to import Magic Lantern MLV into Adobe Premiere Pro

MLV workflow to prepare raw footage for Adobe Premiere Pro

Uncompressed export option includes the following bit depths: 8-bit, 10-bit, 12-bit, 14-bit, 16-bit. For compatibility with Adobe Premiere Pro CC and After Effects, one have to utilize either Uncompressed or Lossless JPEG export options.

Apart from MLV RAW transcoding scenario, we can apply full image processing pipeline to compressed footage from Canon cameras with Magic Lantern firmware in real-time on GPU: native support of DNG/CinemaDNG/MLV formats, fast decoding, high quality debayering, real-time denoising, DCP and LCP profiles, 3D LUT, smooth playback for 4K and much more.

Detailed benchmark data. Measured results are published on our benchmark pages: all benchmarks.

Full version of that pipeline is implemented in Fast CinemaDNG Processor software. Please visit www.fastcinemadng.com

Useful links:

Fyodor Serzhenko, Fastvideo

About the author

Fyodor Serzhenko, PhD, is the founder and CEO of Fastvideo. He earned his PhD at the Moscow Institute of Physics and Technology (MIPT) in 1993. Since 2009 he has led the development of Fastvideo’s GPU-accelerated image codecs and ISP modules, including the Fastvideo SDK. Connect on LinkedIn.

Why you can trust these results

Fastvideo has built GPU-accelerated image processing software since 2009. Our codecs comply with the standards they implement — JPEG (ITU-T T.81 / ISO IEC 10918) and JPEG2000 (ITU-T T.800 / ISO IEC 15444) — and our tools are open source on GitHub. Every performance figure we publish is reproducible: see our benchmark methodology, download the Fastvideo SDK benchmark report (PDF), and measure it on your own GPU.

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