TL;DR: A fixed-rate, near-lossless compression scheme that maps small blocks of 4d values in d dimensions to a fixed, user-specified number of bits per block, thereby allowing read and write random access to compressed floating-point data at block granularity.
Abstract: Current compression schemes for floating-point data commonly take fixed-precision values and compress them to a variable-length bit stream, complicating memory management and random access. We present a fixed-rate, near-lossless compression scheme that maps small blocks of 4(d) values in d dimensions to a fixed, user-specified number of bits per block, thereby allowing read and write random access to compressed floating-point data at block granularity. Our approach is inspired by fixed-rate texture compression methods widely adopted in graphics hardware, but has been tailored to the high dynamic range and precision demands of scientific applications. Our compressor is based on a new, lifted, orthogonal block transform and embedded coding, allowing each per-block bit stream to be truncated at any point if desired, thus facilitating bit rate selection using a single compression scheme. To avoid compression or decompression upon every data access, we employ a software write-back cache of uncompressed blocks. Our compressor has been designed with computational simplicity and speed in mind to allow for the possibility of a hardware implementation, and uses only a small number of fixed-point arithmetic operations per compressed value. We demonstrate the viability and benefits of lossy compression in several applications, including visualization, quantitative data analysis, and numerical simulation.
TL;DR: In this paper, a wireless audio distribution system has a wireless transmitter, responsive to a plurality of audio input channels, for transmitting a encoded digital bitstream serially combining each of the audio input channel, including control data disbursed therein.
Abstract: A wireless audio distribution system having a wireless transmitter, responsive to a plurality of audio input channels, for transmitting a encoded digital bitstream serially combining each of the audio input channel, the encoded digital bitstream further including control data disbursed therein, a receiver, responsive to the transmitted encoded digital bitstream, for decoding and demultiplexing the digital bitstream, a manual selector switch, connected to the receiver device for selecting one or more of the audio input channels to be reproduced, and a sound producing device for selectively reproducing the one or more selected audio channels in accordance with the control data.
TL;DR: This paper proposed two solutions for platform-based design of H.264/AVC intra frame coder with comprehensive analysis of instructions and exploration of parallelism, and proposed a system architecture with four-parallel intra prediction and mode decision to enhance the processing capability.
Abstract: Intra prediction with rate-distortion constrained mode decision is the most important technology in H.264/AVC intra frame coder, which is competitive with the latest image coding standard JPEG2000, in terms of both coding performance and computational complexity. The predictor generation engine for intra prediction and the transform engine for mode decision are critical because the operations require a lot of memory access and occupy 80% of the computation time of the entire intra compression process. A low cost general purpose processor cannot process these operations in real time. In this paper, we proposed two solutions for platform-based design of H.264/AVC intra frame coder. One solution is a software implementation targeted at low-end applications. Context-based decimation of unlikely candidates, subsampling of matching operations, bit-width truncation to reduce the computations, and interleaved full-search/partial-search strategy to stop the error propagation and to maintain the image quality, are proposed and combined as our fast algorithm. Experimental results show that our method can reduce 60% of the computation used for intra prediction and mode decision while keeping the peak signal-to-noise ratio degradation less than 0.3 dB. The other solution is a hardware accelerator targeted at high-end applications. After comprehensive analysis of instructions and exploration of parallelism, we proposed our system architecture with four-parallel intra prediction and mode decision to enhance the processing capability. Hadamard-based mode decision is modified as discrete cosine transform-based version to reduce 40% of memory access. Two-stage macroblock pipelining is also proposed to double the processing speed and hardware utilization. The other features of our design are reconfigurable predictor generator supporting all of the 13 intra prediction modes, parallel multitransform and inverse transform engine, and CAVLC bitstream engine. A prototype chip is fabricated with TSMC 0.25-/spl mu/m CMOS 1P5M technology. Simulation results show that our implementation can process 16 mega-pixels (4096/spl times/4096) within 1 s, or namely 720/spl times/480 4:2:0 30 Hz video in real time, at the operating frequency of 54 MHz. The transistor count is 429 K, and the core size is only 1.855/spl times/1.885 mm/sup 2/.
TL;DR: In this paper, a digital watermarking method and apparatus is proposed for the transmission of a digital video signal in a compressed form, thereby allowing watermark of a pre-compressed video sequence without requiring decoding and re-coding of the signal.
Abstract: A digital watermarking method and apparatus allows for the watermarking of a digital video signal in a compressed form, thereby allowing watermarking of a pre-compressed video sequence without requiring the decoding and re-coding of the signal. The watermark signal is a sequence of information bits which has been modulated by a pseudo-random noise sequence to spread it in the frequency domain. The video signal is transform coded, preferably with a discrete cosine transform, and a watermark signal, which has been transform coded using the same type of transform, is added to the coded video signal. The system also includes bitstream control to prevent an increase in the bit rate of the video signal. This allows the system to be used with transmission channels having strict bit rate constraints. For each transform coefficient of the video signal, the number of bits necessary to encode the watermarked coefficient is compared to the number of bits necessary to encode the unwatermarked coefficient. If more bits are required to transmit a watermarked coefficient than to transmit the corresponding unwatermarked coefficient, the watermarked coefficient is not output, and the unwatermarked coefficient is output in its place. When watermarking interframe coded data, a drift compensation signal may be used to compensate for the accumulating variations in the decoded video signal stored at the receiver. The system may also include an encryption/decryption capability, with the watermarking apparatus located at either the transmitting or receiving end of the transmission channel.
TL;DR: The scalable video coding (SVC) standard as an extension of H.264/AVC allows efficient, standard-based temporal, spatial, and quality scalability of video bit streams.
Abstract: The scalable video coding (SVC) standard as an extension of H.264/AVC allows efficient, standard-based temporal, spatial, and quality scalability of video bit streams. Scalability of a video bit stream allows for media bit rate as well as for device capability adaptation. Moreover, adaptation of the bit rate of a video signal is a desirable key feature, if limitation in network resources, mostly characterized by throughput variations, varying delay or transmission errors, need to be considered. Typically, in mobile networks the throughput, delay and errors of a connection (link) depend on the current reception conditions, which are largely influenced by a number of physical factors. In order to cope with the typically varying characteristics of mobile communication channels in unicast, multicast, or broadcast services, different methods for increasing robustness and achieving quality of service are desirable. We will give an overview of SVC and its relation to mobile delivery methods. Furthermore, innovative use cases are introduced which apply SVC in mobile networks.