Evaluation of image sequence (video) compression with an embedded processing system for future space applications
Date
2024
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Tartu Ülikool
Abstract
In recent years, the accessibility to Graphics Processing Unit (GPU)s and hardware
accelerators for space missions has increased drastically with implementable Commercial
Off-The-Shelf (COTS) solutions. As a result, the onboard computing power has increased
for many space missions, and the performances of the different video compression
methods have been improved. With such evolution in computing resources, it is crucial to
analyze the different methods and record their performances, to find efficient compression
methods in this new configuration. To find efficient compression methods, we developed
a benchmark, to assess multiple methods on their compression ratios, power consumption,
execution time and the difference of quality between the input and output images on a low
resource configuration, adapted for space missions. From the analysis led in this thesis 4,
on the standard codecs, the more lossless the compression, the higher the benefits from
the acceleration. The machine learning approach shows promising results for the future,
and the Consultative Committee for Space Data Systems (CCSDS) 122 despite the GPU
acceleration was outperformed by Advanced Video Coding (H.264) and High-Efficiency
Video Coding (H.265).
Description
Viimastel aastatel on ligipääs graafikakaartidele (GPU) ja riistvarakiirenditele kosmosemissioonide
jaoks suurenenud märkimisväärselt tänu rakendatavatele kommertslahendustele
(COTS). Selle tulemusena on paljude missioonide pardal olev arvutusvõimsus
suurenenud ning erinevate kompressioonimeetodite jõudlus on paranenud. Selle mõjul
on oluline analüüsida erinevaid meetodeid, et tuvastada tõhusaimad meetodid. Selleks
arendasime võrdlusalused mitme meetodi omavaheliseks võrdluseks järgneva alusel:
kompressioonisuhe, energiatarve, täitmisaeg ja kvaliteedi erinevus sisend- ja väljundpiltide
vahel madala ressursikonfiguratsiooni puhul, mis on kohandatud kosmosemissioonide
jaoks. Analüüsist selgub, et standardsete koodekite puhul mida suurema kaoga kompresseeritakse,
seda suuremad on kiirendusest tulenevad eelised. Masinõppe lähenemine
näitab lootustandvaid tulemusi ning CCSDS 122, hoolimata GPU kiirendusest, jäi alla
H.264 ja H.265-le.
Keywords
GPU, hardware accelerator, COTS, CCSDS, H.265, H.264