  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.
