![]() If you need to get significant speed up for your image processing application, don't hesitate to contact us. We are also offering custom software design according to agreed specification. SDK evaluation version, documentation, licensing info and quotation are available upon request. Our SDK is utilized in wide range of high performance imaging applications. We license CUDA Resizer and other components of GPU Image & Video Processing SDK to software developers, camera manufacturers, internet providers, software integrators, etc. Now such a solution is much faster than CPU and FPGA implementations for JPEG Resize. Recently we've got significant performance boost for JPEG Resize with CUDA MPS on Linux. Here you can see more info about JPEG Resizer benchmarks on NVIDIA Tesla V100 and review for the latest solutions and benchmarks on GPU and FPGA. At the final part of such a pipeline we usually apply JPEG Encoder to get output image in jpg format. After that we can apply CUDA Resize and some optional transforms on GPU like Crop, Rotation, Sharpening, etc. That could be also done on GPU with the aid of CUDA JPEG Codec. If we need to resize JPEG images on GPU, we need to decode these images first. We recommend to use our resize solution on CUDA together with other components from our Image Processing SDK to be able to do fast and high quality resize for grayscale or color images. 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 3000 fps. Linux Ubuntu, SLC, RHEL, OpenSUSE, CentOSĬUDA Resizer benchmark on NVIDIA GeForce GTX 1080.Compatible with NVIDIA GPUs Kepler, Maxwell, Pascal, Volta, Turing.Writes resized images to JPEG, BMP, PPM, PGM, DIB formats.Internal calculations with floating point precision.Image resize algorithm for upscale and downscale: Lanczos.Resize images and video to any size quickly and with high quality.Input images: 8-bit or 16-bit per color component RGB, PGM, PPM, BMP, byte array in CPU/GPU memory.Image resizer on CUDA shows outstanding performance with superior quality and this is the best solution for your HPC systems for realtime image processing. ![]() This is fast CUDA Resizer implementation for upscale and downscale, which is now a part of our GPU Image & Video Processing SDK. We have developed extremely fast software to scale grayscale and color images on GPU. ![]()
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