Contextual Video Encoding

Abstract

Digital video compression algorithms exist to preserve the perceptual quality of an input digital video signal, while at the same time reducing the quantity of data necessary to reproduce it. The algorithms that this paper considers are aimed at this objective. Since humans are the consumers of the end result of video compression, by considering human visual perception, irrelevant information can be discarded without a corresponding loss in perceptual quality. Perceptual Video Encoding merges the ideas of digital video compression algorithms and visual perception of quality. Contextual Video Encoding (CVE) is a proposed type of Perceptual Video Encoding which incorporates factors of a video’s viewing environment into the video encoding framework. CVE is an algorithm based on the removal of spatial frequencies of an image depending on user proximity to a video display. The following paper describes how CVE could be implemented alongside existing video encoders in use today by reviewing current literature in the field.

This article was originally written in December 2019 as a senior thesis for my Bachelor’s Degree in Computer Science. When I finished my degree I implemented a PNG still-image encoder based on several concepts that were covered in the paper. I wrote the encoder in C# since I was applying for jobs as a software developer and most of the positions that I applied for were looking for C# programming skills. Since completing this paper I transitioned from working as an Aerial Camera Operator for a major news television network in Philadelphia to working as a Full Stack Web Developer. Today I work on Learning Management Systems, developing Spring Boot/Java back-end applications with the front-end written in Angular/Typescript. I am currently in the process of developing this website, expanding the research paper that you are currently reading, and working on a Java rewrite of version 1.0 of my encoder to accompany this paper. Click here to read more.