An improved variable-length decoder (VLD) architecture which can achieve higher throughput in decoding variable-length codes compared to previously reported VLD architectures is presented. An experimental research pro...
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An improved variable-length decoder (VLD) architecture which can achieve higher throughput in decoding variable-length codes compared to previously reported VLD architectures is presented. An experimental research prototype VLSI implementation of an entropy decoder which includes the VLD and run-length decoder is also discussed. The chip will be fabricated using a 1- mu m double-metal CMOS technology. It is to be used in an experimental prototype high definition television codec with a sample rate of 52 MHz. The chip contains about 46000 transistors in a die size of about 5 mm*5 mm. At 52 MHz, the VLD handles a worst-case input rate of 832 Mb/s and a constant output rate of 416 Mb/s.< >
This paper intends to reduce the power dissipation of the GICam image compressor for capsule endoscope or swallowable imaging capsules while the gastrointestinal images are cardinal. In order to further extend the bat...
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This paper intends to reduce the power dissipation of the GICam image compressor for capsule endoscope or swallowable imaging capsules while the gastrointestinal images are cardinal. In order to further extend the battery life of capsule endoscope, we firstly attempt to analyze the energy distribution and variation of DC/AC coefficients in 2D-DCT domain for twelve tested GI images. According to the analysis results, we can efficiently take advantages of the subsample technique to reduce the memory requirements of green and blue components and hence propose an improved ultra-low-power subsample-based GICam image compressor, called SGICam, to reduce the power dissipation of compression process. Simulation results have been shown that the SGICam image compressor can significantly save 38.5% power dissipation than GICam image one and the average PSNR is 32.18 dB, while the compression ratio can be as low as 4:1.
This paper addresses distributed finite-rate quantized compressed sensing (QCS) acquisition of correlated sparse sources in wireless sensor networks. We propose a distributed variable-rate QCS compression method with ...
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ISBN:
(纸本)9781509017508
This paper addresses distributed finite-rate quantized compressed sensing (QCS) acquisition of correlated sparse sources in wireless sensor networks. We propose a distributed variable-rate QCS compression method with complexity-constrained encoding to minimize a weighted sum of the mean square error distortion of the signal reconstruction and the average encoding rate. The variable-rate coding is realized via entropy-constrained vector quantization, whereas the restrained encoding complexity is obtained via vector pre-quantization of CS measurements. We derive necessary optimality conditions for the system blocks for two-sensor case. Numerical results show that our proposed method efficiently exploits the signal correlation, and achieves superior distortion-rate compression performance.
This paper proposes a high performance hardware architecture design for the H.264/AVC CAVLC encoder. The proposed architecture can make a realtime process for 1920×1080@30p. With the synthesis constraint of a 114...
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This paper proposes a high performance hardware architecture design for the H.264/AVC CAVLC encoder. The proposed architecture can make a realtime process for 1920×1080@30p. With the synthesis constraint of a 114MHz clock, the hardware cost of the proposed design is 7389 gates based on SS65LP 65nm technology.
Rate-distortion optimization (RDO) technique is widely employed by H.264/AVC for the purpose of determining the best mode. However, such technique results in dramatic increase in the computation complexity of the unde...
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Rate-distortion optimization (RDO) technique is widely employed by H.264/AVC for the purpose of determining the best mode. However, such technique results in dramatic increase in the computation complexity of the underlying encoder. In this paper, we address this problem by presenting an efficient intra-4X4 mode decision algorithm. The algorithm works by approximating the bit-rate so as to reduce the computational cost of RDO and the main idea is the following: First we have found a quick way to estimate the bit-rate via the number of DCT coefficients to be quantized to 0 and that to be quantized to +-1. The parameters of the estimated function are adaptively obtained by using the Least Squares Fitting method of the above and the left block in the current frame and the co-location one in the previous encoded frame as the feedback. This close loop bit-rate estimation would skip the processes of quantization, inverse transform, entropy coding and reconstruction;we then use the estimated bit-rate and Sum of Absolute Differences (SAD) to simplify the optimization process of R-D cost function. Experimental results show that our scheme decreases the time for intra coding by 50percent with negligible loss of PSNR, and that comparing with those fast mode-decision algorithms based-on local edge direction, the optimal prediction mode obtained via our scheme is closer to that obtained via the original RDO in statistic.
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