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Selective gray-coded bit-plane based low-complexity motion estimation and its hardware architecture

机译:基于选择性灰度编码的位平面的低复杂度运动估计及其硬件架构

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摘要

Today, many consumer electronics devices have video capturing capability which is one of the most time, power and memory consuming application. Motion estimation (ME) is the key part of the video coding process in terms of computational load. Thus, it is important to implement this process in a resource efficient way without degrading the encoding quality and real-time operation performance. Low bitdepth representation based ME methods draw a lot of attention in consumer electronics area mainly thanks to its highly efficient hardware and software implementations. However, these low bit-depth representation based methods generally assume that the low bit-depth images are already available. Furthermore, these methods simply neglect the binarization cost which is not a proper approach when whole encoding architecture is of concern. This paper presents a novel selective Gray-coding based ME method and its hardware architecture with an embedded system integration by making use of one of the most common interconnect architecture in consumer electronics devices. Experimental results show that it is possible to reduce computational load of binarization stage significantly while improving the ME accuracy by the proposed approach compared to methods at the same category.
机译:如今,许多消费电子设备都具有视频捕获功能,这是最耗时,最耗电和最耗内存的应用之一。就计算量而言,运动估计(ME)是视频编码过程的关键部分。因此,在不降低编码质量和实时操作性能的前提下,以资源高效的方式实施此过程很重要。基于低位深度表示的ME方法主要由于其高效的硬件和软件实现而在消费电子领域引起了广泛关注。但是,这些基于低位深度表示的方法通常假定低位深度图像已可用。此外,这些方法只是忽略了二值化成本,当涉及整个编码体系结构时,这不是适当的方法。本文利用消费电子设备中最常见的互连架构之一,提出了一种新颖的基于选择性格雷编码的ME方法及其具有嵌入式系统集成的硬件架构。实验结果表明,与相同类别的方法相比,该方法可以显着减少二值化阶段的计算量,同时提高ME精度。

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