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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we investigate the impacts of spatial, temporal and amplituderesolution (STAR) on the bit rate of a compressed video. We propose ananalytical rate model in terms of the quantization stepsize, frame size andframe rate. Experimental results reveal that the increase of the video rate asthe individual resolution increases follows a power function. Hence, theproposed model expresses the rate as the product of power functions of thequantization stepsize, frame size and frame rate, respectively. The proposedrate model is analytically tractable, requiring only four content dependentparameters. We also propose methods for predicting the model parameters fromcontent features that can be computed from original video. Simulation resultsshow that model predicted rates fit the measured data very well with highPearson correlation (PC) and small relative root mean square error (RRMSE). Thesame model function works for different coding scenarios (including scalableand non-scalable video, temporal prediction using either hierarchical B or IPPPstructure, etc.) with very high accuracy (average PC $>$ 0.99), but the valuesof model parameters differ. Using the proposed rate model and the quality modelintroduced in a separate work, we show how to optimize the STAR for a givenrate constraint, which is important for both encoder rate control and scalablevideo adaptation. Furthermore, we demonstrate how to order the spatial,temporal and amplitude layers of a scalable video in a rate-quality optimizedway.

Rate Model for Compressed Video Considering Impacts Of Spatial, Temporal  and Amplitude Resolutions and Its Applications for Video Coding and  Adaptation