Digital superconductor electronics has been experiencing rapid maturation with the emergence of smaller-scale, lower-cost communications applications which became the major technology drivers. These applications are primarily in the area of wireless communications, radar, and surveillance as well as in imaging and sensor systems. In these areas, the fundamental advantages of superconductivity translate into system benefits through novel Digital-RF architectures with direct digitization of wide band, high frequency radio frequency (RF) signals. At the same time the availability of relatively small 4 K cryocoolers has lowered the foremost market barrier for cryogenically-cooled digital electronic systems. Recently, we have achieved a major breakthrough in the development, demonstration, and successful delivery of the cryocooled superconductor digital-RF receivers directly digitizing signals in a broad range from kilohertz to gigahertz. These essentially hybrid-technology systems combine a variety of superconductor and semiconductor technologies packaged with two-stage commercial cryocoolers: cryogenic Nb mixed-signal and digital circuits based on Rapid Single Flux Quantum (RSFQ) technology, room-temperature amplifiers, FPGA processing and control circuitry. The demonstrated cryocooled digital-RF systems are the world's first and fastest directly digitizing receivers operating with live satellite signals in X-band and performing signal acquisition in HF to L-band at ~30 GHz clock frequencies.

Inter-channel correlation is one of the redundancy which need to be eliminated in video coding. In the latest video coding standard H.266/VVC, the DM (Direct Mode) and CCLM (Cross-component Linear Model) modes have been introduced to reduce the similarity between luminance and chroma. However, inter-channel correlation is still observed. In this paper, a new inter-channel prediction algorithm is proposed, which utilizes coloring principle to predict chroma pixels. From the coloring perspective, for most natural content video frames, the three components Y, U and V always demonstrate similar coloring pattern. Therefore, the U and V components can be predicted using the coloring pattern of the Y component. In the proposed algorithm, correlation coefficients are obtained in a lightweight way to describe the coloring relationship between current pixel and reference pixel in Y component, and used to predict chroma pixels. The optimal position for the reference samples is also designed. Base on the selected position of the reference samples, two new chroma prediction modes are defined. Experiment results show that, compared with VTM 12.1, the proposed algorithm has an average of -0.92% and -0.96% BD-rate improvement for U and V components, for All Intra (AI) configurations. At the same time, the increased encoding time and decoding time can be ignored.