KEYWORDS: Video, 3D modeling, Eye models, Telecommunications, Video compression, Image compression, RGB color model, Systems modeling, Eye, Data modeling
Emerging communications trends point to streaming video as a new form of content delivery. These systems are
implemented over wired systems, such as cable or ethernet, and wireless networks, cell phones, and portable game
systems. These communications systems require sophisticated methods of compression and error-resilience encoding to
enable communications across band-limited and noisy delivery channels. Additionally, the transmitted video data must
be of high enough quality to ensure a satisfactory end-user experience. Traditionally, video compression makes use of
temporal and spatial coherence to reduce the information required to represent an image. In many communications
systems, the communications channel is characterized by a probabilistic model which describes the capacity or fidelity
of the channel. The implication is that information is lost or distorted in the channel, and requires concealment on the
receiving end. We demonstrate a generative model based transmission scheme to compress human face images in video,
which has the advantages of a potentially higher compression ratio, while maintaining robustness to errors and data
corruption. This is accomplished by training an offline face model and using the model to reconstruct face images on the
receiving end. We propose a sub-component AAM modeling the appearance of sub-facial components individually, and
show face reconstruction results under different types of video degradation using a weighted and non-weighted version
of the sub-component AAM.
We report AlGaN-based back-illuminated solar-blind p-i-n photodetectors with a record peak responsivity of 150 mA/W at 280 nm, corresponding to a high external quantum efficiency of 68%, increasing to 74% under 5 volts reverse bias. Through optimization of the p-AlGaN layer, we were able to remove the out-of-band negative photoresponse originating from the Schottky-like p-type metal contact, and hence significantly improve the degree of solar-blindness. We attribute the high efficiency of these devices to the use of very-high quality AlN and Al0.87Ga0.13N/AlN superlattice material, a highly conductive Si-In co-doped Al0.5Ga0.5N layer, and the elimination of the negative photoresponse through improvement of the p-type AlGaN.
We demonstrate high power AlGaN based ultraviolet light-emitting diodes (UV LEDs) with an emission wavelength of 280 nm using an asymmetric single quantum well active layer configuration on top of a high-quality AlGaN/AlN template layer grown by metalorganic chemical vapor deposition (MOCVD). An output power of 1.8 mW at a pulsed current of 400 mA was achieved for a single 300 μm × 300 μm diode. This device reached a high peak external quantum efficiency of 0.24% at 40 mA. An array of four diodes produced 6.5 mW at 880 mA of pulsed current. We also demonstrate high output power operation of AlGaN-based UV LEDs at a short wavelength of 265 nm. An output power of 2.4 mW at a pulsed current of 360 mA was achieved for a single diode. A packaged array of four diodes produced 5.3 mW at 700 mA of pulsed current. The DC output power is 170 μW at 250 mA.
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