This paper addresses the problem of encoding the video generated by the screen of an airplane cockpit. As other computer screens, cockpit screens consist of computer-generated graphics often atop a natural background. Existing screen content coding schemes fail notably in preserving the readability of textual information at the low bitrates required in avionic applications. We propose a screen coding scheme where textual information is encoded according to the relative semantics rather than in the pixel domain. The encoder localizes textual information, and the semantics of each character are extracted with a convolutional neural network and predictively encoded. Text is then removed via inpainting, and the residual background video is compressed with a standard codec and transmitted to the receiver together with the text semantics. At the decoder side, text is synthesized using the decoded semantics and superimposed over the decoded residual video recovering the original frame. Our proposed scheme offers two key advantages over a semantics-unaware scheme that encodes text in the pixel domain. First, the text readability at the decoder is not compromised by compression artifacts, whereas the relative bitrate is negligible. Second, removal of high-frequency transform coefficients associated with the inpainted text drastically reduces the bitrate of the residual video. Experiments with real cockpit video sequences show BD-rate gains up to 82% and 69% over a reference H.265/HEVC encoder and its screen content coding extension. Moreover, our scheme achieves quasi-errorless character recognition already at very low bitrates, whereas even HEVC-SCC needs at least three or four times more bitrate to achieve a comparable error rate.

This paper presents the design of an Ultra Low Power (ULP) inductorless Low Noise Amplifier (LNA) based on a Common Gate (CG) architecture using the back gate control of the Fully-Depleted Silicon-On-Insulator (FDSOI) technology. It demonstrates the potential of the back biasing to lower the power consumption of more than 30 % compared to a design without back biasing, while keeping similar performance. This paper also shows the possibility with the back gate control of this technology to reach additional performance, suitable for the design of tunable LNAs. The proposed LNA has been implemented in ST-Microelectronic 28 nm FDSOI Technology and its active area is only 0.0015 mm2. The measured performance exhibit more than 16 dB of voltage Gain (Gv), 7.3 dB of Noise Figure (NF) and an Input referred third-order Intercept Point (IIP3) of -16 dBm. The total power consumption is 300 μW from a 0.6 V supply. The same LNA reached other performance modes at constant Figure of Merit (FoM).