视频压缩与传输的多目标优化框架

A. Al-Najdawi, R. Kalawsky
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引用次数: 2

摘要

在低带宽信道的视频传输中,需要保证高质量的视频和足够的信道吞吐量。过去二十年见证了无线通信技术的空前发展。事实证明,对带宽资源的竞争非常激烈,自动驾驶汽车的车载功率和重量限制限制了最大数据传输速率。这些因素突出了对非常有效的数据压缩方案的迫切需求。图像往往是带宽最密集的数据;因此,图像和视频压缩方法尤为有价值。在本文中,作者提出了一种新的优化视频压缩的技术,同时不损害视觉质量。这为自动驾驶汽车返回的图像和视频的视觉质量评估领域开辟了新的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-objective optimization framework for video compression and transmission
In video transmission over low-bandwidth channels, high-quality video and sufficient channel throughput should be guaranteed. The last two decades have witnessed an unprecedented growth of wireless communication technologies. It turned out that competition for bandwidth resources is fierce, and onboard power and weight constraints in autonomous vehicles limit the maximum data transmission rates. These factors highlight a critical need for very effective data compression schemes. Images tend to be the most bandwidth-intensive data; therefore, image and video compression methods are particularly valuable. In this paper, the authors present a novel technique for optimizing video compression while visual quality is not compromised. This opens up new scopes in the domain of visual quality assessment of images and videos returned from autonomous vehicles.
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