fast CUDA resizer

CUDA Resizer from Fastvideo

We have developed extremely fast software to scale grayscale and color images on GPU. This is fast CUDA Resizer implementation, which is now a part of our GPU Image & Video Processing SDK. Image resizer on CUDA shows outstanding performance with superior quality and this is the best solution for your HPC systems for realtime image processing.

CUDA Resizer Features

  • Input images: 8-bit or 16-bit per color component RGB, PGM, PPM, BMP, JPEG formats, byte array in CPU/GPU memory
  • Resize images and video to any size quickly and with high quality
  • Image resize algorithm: Lanczos
  • Internal calculations with floating point precision
  • Writes resized images in JPEG, BMP, PPM, PGM, DIB formats
  • Compatible with NVIDIA GPUs Fermi, Kepler, Maxwell and Pascal

OS Supported

  • Windows-7/8/10
  • Linux Ubuntu, SLC 6.5, RHEL 6.5, OpenSUSE 12
  • Linux4Tegra (L4T)

CUDA Resizer benchmark on NVIDIA GeForce GTX Titan X

High quality image resize for color Full HD (1920×1080, 24-bit) image to final resolution 960×576 can be done on NVIDIA GeForce GTX 1080 GPU at frame rate 2600 fps. We recommend to use our resize solution on CUDA together with other components from our Image & Video Processing SDK to be able to do fast and high quality resize for grayscale or color images.


We license CUDA Resizer and other components of GPU Image & Video Processing SDK to software developers, camera manufacturers, internet providers, software integrators, etc. Our SDK is utilized in wide range of high performance imaging applications. SDK evaluation version, documentation, licensing info and quotation are available upon request. We are also offering custom software design according to agreed specification. If you need to get significant speed up for your image processing application, don't hesitate to contact us.

Roadmap for further improvements of CUDA Resizer

  • CUDA Resizer integration into Fast CinemaDNG Processor software - done
  • Minimum memory usage on CUDA applications
  • More input/output formats for CUDA Resizer
  • New high quality image resize algorithm on CUDA
  • Other CUDA Resizer optimizations for Maxwell and Pascal

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