This paper proposes a framework for joint source-channel decoding of Markov sequences that are encoded by an entropy coded multiple description quantizer (MDQ), and transmitted via a lossy network. This framework is p...
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This paper proposes a framework for joint source-channel decoding of Markov sequences that are encoded by an entropy coded multiple description quantizer (MDQ), and transmitted via a lossy network. This framework is particularly suited for lossy networks of inexpensive energy-deprived mobile source encoders. Our approach is one of maximum aposteriori probability (MAP) sequence estimation that exploits both the source memory and the correlation between different MDQ descriptions. The MAP problem is modeled and solved as one of the longest path in a weighted directed acyclic graph. For MDQ-compressed Markov sequences impaired by both bit errors and erasure errors, the proposed joint source-channel MAP decoder can achieve 5 dB higher SNR than the conventional hard-decision decoder. Furthermore, the new MDQ decoding technique unifies the treatments of different subsets of the K descriptions available at the decoder, circumventing the thorny issue of requiring up to 2 K -1 MDQ side decoders
A common approach for video transrating (bit rate reduction) is to requantize the transform coefficients. Optimal requantization aims to find a set of new step-sizes that achieve the target bit rate while introducing ...
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A common approach for video transrating (bit rate reduction) is to requantize the transform coefficients. Optimal requantization aims to find a set of new step-sizes that achieve the target bit rate while introducing minimal distortion. Since the state of the art H.264 standard coder constrains requantization by limiting the amount of change in the quantization step-size from one macroblock to the next, the common Lagrangian optimization approach cannot be applied. We propose a solution to this dependency problem by extending each Lagrangian iteration with a constrained dynamic programming stage. Further, in order to reduce the computational load of evaluating the rate and distortion at each macroblock for multiple step-sizes, we suggest analytic models that can be applied for this purpose. The developed models are suitable for requantization and are matched to the context-adaptive entropy coding used in H.264. The proposed algorithm performs the requantization in the compressed domain and currently supports inter coded frames only. It reduces the run-time by a factor of 4, as compared to the full exhaustive optimization, and achieves up to 1[dB] gain in PSNR, as compared to a simple one-pass algorithm.
Inter-color correlation between the luminance component and chrominance components has been utilized for color image coding for years. However, the correlation has not been clearly analyzed. In this paper, we analyze ...
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Inter-color correlation between the luminance component and chrominance components has been utilized for color image coding for years. However, the correlation has not been clearly analyzed. In this paper, we analyze the inter-color correlation and answer two questions related to color image coding: (1) what kind of inter-color correlation exists in color images after the discrete wavelet transform?; and, (2) how strong is it? This analysis helps us to find a most suitable inter-color context and eventually leads to a new embedded color image codec. By using the discovered inter-color context, significant performance improvement can be achieved when encoding chrominance components.
Intra prediction is an effective method for reducing the coded information of an image or an intra frame within a video sequence. The conventional method today is to create a sample predictor block by extrapolating th...
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Intra prediction is an effective method for reducing the coded information of an image or an intra frame within a video sequence. The conventional method today is to create a sample predictor block by extrapolating the reconstructed pixels surrounding the target block to be coded. The sample predictor block is subtracted from the target block and the resulting residual coded using transformation, quantization and entropy coding. This is an effective method for sample predictor block creation in most sequences. However the extrapolation method is not able to represent sample prediction blocks with complex texture. Furthermore, pixels that are far from the surrounding pixels are usually badly predicted. In this paper, a new method for sample predictor creation by template matching in a region of reconstructed pixels is presented. Improvements in coding efficiency by more than 11% in bitrate were achieved.
In recent years, wavelet-based image and video coding systems that utilize a wide range of spatial-temporal-SNR scalability with state-of-the-art coding performance has been proposed in the literature. The strong mark...
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In recent years, wavelet-based image and video coding systems that utilize a wide range of spatial-temporal-SNR scalability with state-of-the-art coding performance has been proposed in the literature. The strong market acceptance of the new scalable technology stems from advances in network technology as well as various requirements from terminal users since computer network is becoming the main media transmission. This paper presents a simplified scalable wavelet video coding structure using MCTF with 5/3 filter. This structure does not include motion estimation, hence entropy coding for motion vectors is omitted. The proposed codec generates four temporal resolution layers, with up to four spatial resolution levels and six variable quantization levels for certain sequence. Simulation results show the codec has great flexibility feature and the reconstructed video quality is thought to be of acceptable quality
Channel-optimized quantizer index assignment and maximum a posteriori (MAP) decoding have been extensively studied for error-resilient communications. An interesting and largely untreated problem is how to optimize th...
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Channel-optimized quantizer index assignment and maximum a posteriori (MAP) decoding have been extensively studied for error-resilient communications. An interesting and largely untreated problem is how to optimize the index assignment with respect to joint source-channel MAP decoding. In this paper we formulate the above problem as one of quadratic programming, and discuss its solutions from very general to some special cases. Experimental results are presented to demonstrate the performance improvement of the index assignments optimized for MAP decoding over those designed for hard-decision decoding.
The most computationally intensive part of wide-band receivers is the IF processing block. Digital filtering is the main task in IF processing. Infinite precision filters require complicated digital circuits due to co...
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The most computationally intensive part of wide-band receivers is the IF processing block. Digital filtering is the main task in IF processing. Infinite precision filters require complicated digital circuits due to coefficient multiplication. This paper presents an efficient method to implement pulse shaping filters for a dual-mode GSM/W-CDMA receiver. We use an arithmetic scheme, known as pseudo floating-point (PFP) representation to encode the filter coefficients. By employing a span reduction technique, we show that the filters can be coded using an optimal entropy scheme employing PFP which requires only considerably fewer bits than conventional 24-bit and 16-bit fixed-point filters. Simulation results show that the magnitude responses of the filters coded in PFP meet the attenuation requirements of GSM/W-CDMA specifications.
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.
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