论文标题
块调制视频压缩：资源有限平台的超低复杂性图像压缩编码器
Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms
论文作者
论文摘要
我们考虑资源有限平台上的图像和视频压缩。一个超低成本的图像编码器，名为“块调制视频压缩（BMVC）”具有编码复杂性$ {\ cal o}（1）$的$，提议在低消耗功率和计算资源的移动平台上实现。我们还开发了由深神经网络实施的两种类型的BMVC解码器。第一个BMVC解码器基于插件播放（PNP）算法，该算法具有不同的压缩比。第二个解码器是一种内存有效的端到端卷积神经网络，旨在实时解码。高清图像和视频的广泛结果证明了拟议的编解码器的出色性能以及抗位量化的鲁棒性。
We consider the image and video compression on resource limited platforms. An ultra low-cost image encoder, named Block Modulating Video Compression (BMVC) with an encoding complexity ${\cal O}(1)$ is proposed to be implemented on mobile platforms with low consumption of power and computation resources. We also develop two types of BMVC decoders, implemented by deep neural networks. The first BMVC decoder is based on the Plug-and-Play (PnP) algorithm, which is flexible to different compression ratios. And the second decoder is a memory efficient end-to-end convolutional neural network, which aims for real-time decoding. Extensive results on the high definition images and videos demonstrate the superior performance of the proposed codec and the robustness against bit quantization.
