This is Fastvideo blog about image compression and decompression, demosaicing, denoising, tone mapping, color correction, resizing, sharpening, encoding and decoding of video streams in various applications including image and video processing, transcoding, streaming, broadcasting, high speed imaging, machine vision, digital cinema, 3D and VR, etc.
Benchmarks of Discrete Wavelet Transform on CUDA
DWT performance benchmarks on NVIDIA GeForce GTX 1080 for CDF 9/7 and CDF 5/3 wavelets on 24-bit images (8-bit at each of 3 color channels) for different image sizes (up to 8K Ultra HD image resolution).
High Performance Image Processing for Industry-4.0
GPU-based image processing can significantly improve both performance and image quality in industrial vision applications. This is important step towards faster imaging solutions.
How to prepare video training set for AI application?
AI applications are increadibly popular nowadays. They could solve various very complicated tasks and quite often they can do that much better than humans. This is the fact and we see that the number of such applications is growing rapidly. Let's consider the situation from inside, just to understand how it goes and what do we need to proceed with AI solutions.
Fastvideo SDK benchmarks on NVIDIA Quadro RTX 6000
We've done testing of Fastvideo SDK on NVIDIA® Quadro RTX™ 6000 which is powered by the NVIDIA Turing™ architecture and NVIDIA RTX™ platform. That new technology brings the most significant advancement in computer graphics in over a decade to professional workflows. That new hardware is intended to boost the performance of image and video processing dramatically.
Low latency H.264 streaming on Jetson TX2
Realtime remote control for any vision system is very important task which has a huge number of applications. People need to control remotely almost everything. To make it possible, we need to create a solution with minimum latency to ensure smooth video and instant feedback. There are a lot of imaging systems which rely on small feedback time, like autonomous cars, hexacopters or drones, mobile robots that should be remotely controlled via wireless network, etc.
GPU software for camera applications
There are many machine vision and industrial cameras with high resolution and high frame rate image sensors. These cameras generate huge amount of data and it's a challenge to cope with them properly. GPU-based image processing is the key to achieve both realtime performance and high quality, especially for multicamera systems.
Jetson zero-copy for embedded applications
Zero-copy means that we don't need to spend any time to copy data from host to device over PCIE, as we always have to do on any discrete laptop/desktop/server GPU. Basically, this is the way of how integrated GPU can take an advantage of DMA, shared memory and caches.
Realtime image processing on GPU for XIMEA CB500
High resolution cameras are getting more and more popular nowadays with resolution parameter ever growing due to advancement in the latest image sensor technology. The newest of them offer remarkable resolution of 50 or more Megapixel pushing the data bandwidth to the edge where it can become a bottleneck.
JPEG2000 vs JPEG vs PNG: What's the Difference?
If you look for a list of image format standards with good compression ratio, a simple Google search will yield a lot of results. JPEG and the similar sounding JPEG2000, along with PNG, are among the best image compression formats today.
Jetson image processing: ISP libargus and Fastvideo SDK
How to build a camera system on Jetson? This is an important task if you want to create realtime solution for mobile imaging application. With a thoughtful design, one can even implement a multicamera system on just a single Jetson, and some NVIDIA partners showcase that this is in fact achievable.
Jetson TX2 and AGX Xavier performance comparison
Imaging applications benefit from the latest NVIDIA mobile GPUs: Jetson TX2 and AGX Xavier. Nevertheless, general benchmarks can't answer the question about performance comparison for the latest NVIDIA Jetson hardware. Anyway, this is very practical issue for many imaging applications, including aerial imaging, UAV, robotics, self-driving cars, etc. To provide you with real numbers, we've done comparative studies with Fastvideo SDK, which has lots of image processing modules for camera applications.
JPEG Resize for WEB
In various imaging applications we have to do image resize and quite often we need to resize JPEG images. In such a case the task gets more complicated, as soon as we can't do resize directly, because images are compressed.
Fastvideo SDK benchmarks 2018
Fastvideo SDK benchmarks 2018: JPEG encoding and decoding, demosaicing, JPEG2000 encoding, denoising, resizing on NVIDIA Jetson TX1, TX2 and AGX Xavier, GeForce GTX 1080, Quadro P6000.