Utilizing Massive Compute Resources in the Public Cloud for Complex Image Processing

Richard Welsh

This paper explores the deployment of complex image processing applications in a public cloud to make massive processing jobs practical for post-production budgets and timescales. It uses an illustrative example of an iterative motion-compensated super-resolution pixel reconstruction technique deployed in a cloud platform that can process what was an 8-week job on local hardware in a few hours using a public cloud. However, the technique is not without its pitfalls. Even large public cloud data centers have practical limits that cannot be ignored. Real-world examples range from 35-mm restoration for digital 3D re-release to the latest Hollywood 120 frames/sec, 4K, 3D high-dynamic-range content. Large-scale resources can be leveraged for otherwise impractical techniques, opening the door to a new breed of high-end media processing tools and making them accessible to post-production facilities.

Print ISSN
Electronic ISSN
2160-2492
Published
2016-10
Content type
Original Research
Keywords
cloud, massive scale computation, scaling, virtualization, image processing applications, software platform, post production, sundog media toolkit, software as a service, SaaS, Platform as a Service, PaaS, Infrastructure as a Service, IaaS, object storage, encryption, security, tools, processing, on demand, data center, on premise, public cloud, private cloud, hybrid cloud, infrastructure, restoration, enhancement
DOI
10.5594/JMI.2016.2602122