ALTMapper: Adaptive Local Tone Mapping Software

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ALTMapper is adaptive local tone mapping software for images on disk. It recovers shadow detail, controls local contrast and removes haze with 32-bit ISP accuracy, using a classical per-pixel transform — no neural networks and no hallucinated detail, so the same input always gives the same output. It ships as a GUI application for interactive work and a CLI application with Python control for batch processing. How the algorithm works is described on the Tonemap page.

ALTMapper — Adaptive Local Tone Mapping on the Fastvideo CUDA SDK

ALTMapper Features

See the difference

ALTMapper before and after: source image on the left, adaptive local tone mapping result on the right

Source image on the left, ALTMapper result on the right — recovered shadow detail and controlled local contrast, with no halos and no hallucinated detail.

Compatibility

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Applications

ALTMapper Roadmap

ALTMapper is a mature tone-mapping engine in active development. Delivered in recent releases (2025–2026):

Current development focuses on:

Licensing

Tell us how many machines you run and how the work is organized, and we will send a quotation.

Options beyond the license

The license gives you the software as it ships. In real production most installations also take one or more one-time options.

Optimization. The same task can be built in several ways: a shorter pipeline that runs faster, or a fuller one that produces a better image; with or without calibration steps; on hardware chosen to match. Whichever chain you settle on becomes the image quality your system delivers for as long as it stays in service, in every place it is deployed and to everyone who uses it. It is a decision made once and lived with for years — we make it with you, before it is fixed in your product.

Precise tuning. Parameters set for your cameras, your optics and your shooting conditions, so that the result is repeatable instead of adjusted by hand each time.

Each of these is built for your setup, so there is no off-the-shelf version. Tell us how your process runs today and what is still done by hand, and we will tell you which options are worth taking. One-time fee, quoted together with the license.

ALTMapper FAQ

What is adaptive local tone mapping?

It is a per-pixel, spatially adaptive transform that compresses a high dynamic range into a displayable range while preserving local contrast and fine detail. Unlike a single global curve, ALTMapper adapts to each region of the image, so it lifts shadows and tames highlights without flattening texture.

Does ALTMapper use AI or neural networks?

No. ALTMapper is a deterministic classical algorithm and does not invent or hallucinate detail. The same input always produces the same output — important for machine vision, measurement, and broadcast pipelines that need repeatable results.

How fast is ALTMapper?

The ALTMapper application works with files on disk, and most of the time goes to disk reads, JPEG decoding and re-encoding rather than to tone mapping itself — so it is not the right tool for measuring the speed of the algorithm. The GPU figures, a 65 MPix frame in 6.3 ms on an RTX 4090, belong to Tonemap running inside a GPU pipeline where the data stays in video memory.

Can I run it inside my own GPU pipeline, or on NVIDIA Jetson?

That is Tonemap, the same algorithm as a module of the Fastvideo SDK. It runs on desktop NVIDIA GPUs and on the Jetson line under Linux4Tegra.

Can ALTMapper process video?

Yes. It includes flicker reduction for video tone mapping, so brightness and contrast stay temporally stable from frame to frame.

How can I try it?

Download the ALTMapper demo for Windows and run it on your own images: that is how you judge the image quality, on your data rather than on ours. To measure speed, use Tonemap in the Fastvideo SDK or run the whole pipeline in FastVCR.

Related: how the underlying local tone mapping algorithm works on GPU, and side-by-side video demos on ARRI Alexa LogC cinema footage and a XIMEA 8.9 MPix camera.

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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