English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Good quality video coding for low bit-rate applications is important fortransmission over narrow-bandwidth channels and for storage with limited memorycapacity. In this work, we develop a previous analysis for image compression atlow bit-rates to adapt it to video signals. Improving compression usingdown-scaling in the spatial and temporal dimensions is examined. We show, boththeoretically and experimentally, that at low bit-rates, we benefit fromapplying spatio-temporal scaling. The proposed method includes down-scalingbefore the compression and a corresponding up-scaling afterwards, while thecodec itself is left unmodified. We propose analytic models for low bit-ratecompression and spatio-temporal scaling operations. Specifically, we usetheoretic models of motion-compensated prediction of available and absentframes as in coding and frame-rate up-conversion (FRUC) applications,respectively. The proposed models are designed for multi-resolution analysis.In addition, we formulate a bit-allocation procedure and propose a method forestimating good down-scaling factors of a given video based on its second-orderstatistics and the given bit-budget. We validate our model with experimentalresults of H.264 compression.

Improving Low Bit-Rate Video Coding using Spatio-Temporal Down-Scaling