Recently, foveated 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 FPSNR 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.
Bibliographical noteFunding Information:
Manuscript received November 18, 1998; revised March 28, 2001. This work was supported in part by Bell Labs, Lucent Technologies, Texas Instruments Inc., and by the Texas Advanced Technology Program. The associate editor co-ordinating the review of this manuscript and approving it for publication was Dr. Boon-Lock Yeo.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design