Abstract
The heavy memory access of motion estimation (ME) execution consumes significant power and could limit ME execution when the available memory bandwidth (BW) is reduced because of access congestion or changes in the dynamics of the power environment of modern mobile devices. In order to adapt to the changing BW while maintaining the rate-distortion (R-D) performance, this article proposes a novel data BW-scalable algorithm for ME with mobile multimedia chips. The available BW is modeled in a R-D sense and allocated to fit the dynamic contents. The simulation result shows 70% BW savings while keeping equivalent R-D performance compared with H.264 reference software for low-motion CIF-sized video. For high-motion sequences, the result shows our algorithm can better use the available BW to save an average bit rate of up to 13% with up to 0.1-dB PSNR increase for similar BW usage.
Highlights
With the rapid progress of semiconductor technology, video coding is becoming popular in modern mobile devices to provide video services
Motion-compensated temporally predictive coding with motion estimation (ME) contributes the most to the coding efficiency of modern video encoder designs [1], and requires large amounts of computations as well as data bandwidth (BW) [2]
We introduce a set of BW control parameters, B = [b1,b2,...,bL], to control the search area of the ME module
Summary
With the rapid progress of semiconductor technology, video coding is becoming popular in modern mobile devices to provide video services. In power-limited mobile device, the available power could be changed dynamically due to low battery power or dynamic power management, such as dynamic voltage and frequency scaling [2,3] In such cases, the available data BW could be inconsistent with the video requirements and be lower than expected. Bus BW-effective ME designs in [20,21] lower the BW requirement by reducing the pixel representation from 8 bits to a binary pattern These designs are only useful for specific search algorithms without a data BW constraint. Once the optimum BW efficiency of the previous coded MB is determined, we need to develop a scheme to allocate and predict the BW interval to achieve the video smoothness constraint This approach is computationally intensive and its corresponding parameter adjustment is only suitable for offline analysis. For the purposes of having a concrete example that represents common practices in video coding, the BW budget for the GOP is set 16 frames in this article
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