Video Chunk Processor: Low-Latency Parallel Processing of 3 x 3-pixel Image Kernels

Citation

Kho, Daniel Cheok Kiang and Ahmad Fauzi, Mohammad Faizal and Lim, Sin Liang (2022) Video Chunk Processor: Low-Latency Parallel Processing of 3 x 3-pixel Image Kernels. International Journal of Technology, 13 (5). p. 1045. ISSN 2086-9614

[img] Text
11.pdf - Published Version
Restricted to Repository staff only

Download (1MB)

Abstract

Video framebuffers are usually used in video processing systems to store an entire frame of video data required for processing. These framebuffers make extensive use of random access memory (RAM) technologies and interfaces that use them. Recent trends in the high-speed video discuss the use of higher speed memory interfaces such as DDR4 (double-datarate 4) and HBM (high-bandwidth memory) interfaces. To meet the demand for higher image resolutions and frame rates, larger and faster framebuffer memories are required. While it is not feasible for software to read and process parts of an image quickly and efficiently enough due to the high speed of the incoming video, a hardware-based video processing solution poses no such limitation. Existing discussions involve the use of framebuffers even in hardware-based implementations, which greatly reduces the speed and efficiency of such implementations. This paper introduces hardware techniques to read and process kernels without the need to store the entire image frame. This reduces the memory requirements significantly without losing the quality of the processed images.

Item Type: Article
Uncontrolled Keywords: Framebuffer, Image processing, Kernel processing, Parallel processing, Video processing
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 27 Oct 2022 03:48
Last Modified: 27 Oct 2022 03:48
URII: http://shdl.mmu.edu.my/id/eprint/10557

Downloads

Downloads per month over past year

View ItemEdit (login required)