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Foveated video compression with optimal rate control

Published: 01 July 2001 Publication History

Abstract

Previously, fovcated video compression algorithms have been proposed which, in certain applications, deliver high-quality video at reduced bit rates by seeking to match the nonuniform sampling of the human retina. We describe such a framework here where foveated video is created by a nonuniform filtering scheme that increases the compressibility of the video stream. We maximize a new foveal visual quality metric. the foveal signal-to-noise ratio (FSNR) to determine the best compression and rate control parameters for a given target bit rate. Specifically, we establish a new optimal rate control algorithm for maximizing the FSNR using a Lagrange multiplier method defined on a curvilinear coordinate system. For optimal rate control, we also develop a piecewise R-D (rate-distortion)/R-Q (rate-quantization) model. A fast algorithm for searching for an optimal Lagrange multiplier λ* is subsequently presented. For the new models, we show how the reconstructed video quality is affected, where the FSNR is maximized, and demonstrate the coding performance for H.263,+,++/MPEG-4 video coding. For H.263/MPEG video coding, a suboptimal rate control algorithm is developed for fast, high-performance applications. In the simulations, we compare the reconstructed pictures obtained using optimal rate control methods for foveated and normal video. We show that foveated video coding using the suboptimal rate control algorithm delivers excellent performance under 64 kb/s

Cited By

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  • (2023)Foveated Spatial Compression for Remote Rendered Virtual RealityProceedings of the First Workshop on Metaverse Systems and Applications10.1145/3597063.3597359(7-13)Online publication date: 18-Jun-2023
  • (2022)Towards retina-quality VR video streamingACM SIGCOMM Computer Communication Review10.1145/3523230.352323352:1(10-19)Online publication date: 1-Mar-2022
  • (2021)Subjective and Objective Quality Assessment of 2D and 3D Foveated Video Compression in Virtual RealityIEEE Transactions on Image Processing10.1109/TIP.2021.308732230(5905-5919)Online publication date: 1-Jan-2021
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      cover image IEEE Transactions on Image Processing
      IEEE Transactions on Image Processing  Volume 10, Issue 7
      July 2001
      164 pages

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      IEEE Press

      Publication History

      Published: 01 July 2001

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      • (2023)Foveated Spatial Compression for Remote Rendered Virtual RealityProceedings of the First Workshop on Metaverse Systems and Applications10.1145/3597063.3597359(7-13)Online publication date: 18-Jun-2023
      • (2022)Towards retina-quality VR video streamingACM SIGCOMM Computer Communication Review10.1145/3523230.352323352:1(10-19)Online publication date: 1-Mar-2022
      • (2021)Subjective and Objective Quality Assessment of 2D and 3D Foveated Video Compression in Virtual RealityIEEE Transactions on Image Processing10.1109/TIP.2021.308732230(5905-5919)Online publication date: 1-Jan-2021
      • (2021)Video Compression for Screen Recorded Sequences Following Eye MovementsJournal of Signal Processing Systems10.1007/s11265-021-01719-293:12(1457-1465)Online publication date: 1-Dec-2021
      • (2020)Dynamic Receptive Field Generation for Full-Reference Image Quality AssessmentIEEE Transactions on Image Processing10.1109/TIP.2020.296828329(4219-4231)Online publication date: 7-Feb-2020
      • (2019)DeepFoveaACM Transactions on Graphics10.1145/3355089.335655738:6(1-13)Online publication date: 8-Nov-2019
      • (2019)Deep Visual Saliency on Stereoscopic ImagesIEEE Transactions on Image Processing10.1109/TIP.2018.287940828:4(1939-1953)Online publication date: 1-Apr-2019
      • (2018)Kernel Foveated RenderingProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/32031991:1(1-20)Online publication date: 25-Jul-2018
      • (2018)Deep Video Quality Assessor: From Spatio-Temporal Visual Sensitivity to a Convolutional Neural Aggregation NetworkComputer Vision – ECCV 201810.1007/978-3-030-01246-5_14(224-241)Online publication date: 8-Sep-2018
      • (2017)Enhancement of Visual Comfort and Sense of Presence on Stereoscopic 3D ImagesIEEE Transactions on Image Processing10.1109/TIP.2017.270238326:8(3789-3801)Online publication date: 1-Aug-2017
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