We explore the performance of two dimensional (2-D) prediction based LSF quantization method for both wide-band and telephone-band (narrow-band) speech. The 2-D prediction based method exploits both the inter-frame an...
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We explore the performance of two dimensional (2-D) prediction based LSF quantization method for both wide-band and telephone-band (narrow-band) speech. The 2-D prediction based method exploits both the inter-frame and intra-frame correlations of LSF parameters. We show that a 4th order 2-D predictor provides optimum prediction gain as well as improved quantization performance at various choices of frame shift for both wide-band and telephone-band speech. Existing one dimensional (1-D) predictive method, exploiting only inter-frame correlation, results in poor performance at larger frame shifts; whereas proposed 2-D predictor provides lower spectral distortion as well as lower number of outliers compared to existing memory-based and memory-less methods.
Many important developments in video compression technologies have occurred during the past two decades. The block-based discrete cosine transform with motion compensation hybrid coding scheme has been widely employed...
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Many important developments in video compression technologies have occurred during the past two decades. The block-based discrete cosine transform with motion compensation hybrid coding scheme has been widely employed by most available video coding standards, notably the ITU-T H.26x and ISO/IEC MPEG-x families and video part of China audio video coding standard (AVS). The objective of this paper is to provide a review of the developments of the four basic building blocks of hybrid coding scheme, namely predictive coding, transform coding, quantization and entropy coding, and give theoretical analyses and summaries of the technological advancements. We further analyze the development trends and perspectives of video compression, highlighting problems and research directions.
Functional magnetic resonance imaging (fMRI) and neuron electrophysiology (neurophysiology) are two well-established ways to measure brain activity. Even though the spatial and temporal resolution of these techniques ...
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Functional magnetic resonance imaging (fMRI) and neuron electrophysiology (neurophysiology) are two well-established ways to measure brain activity. Even though the spatial and temporal resolution of these techniques is very different, both measurements show a high level of consistency, i.e., for mapping feature preferences of cortical areas. There are, however, other striking differences between fMRI and neurophysiology, for example, fMRI has good accessibility to higher cognitive functions, a bias to measure synaptic activity, and a good sensitivity to detect feedback-related activity, all of which can shed a new light on the function of well-known brain areas like primary visual cortex, V1. Classically, it is believed that V1 cells are exhaustively characterized by their complex receptive field properties. Contrary to this view, however, fMRI shows that response properties in area V1 are spatially unstable, influenced by contextual information, and depend on internal states. This review will highlight some of the most striking new fMRI findings that show Vi is involved in higher cognitive functions. (C) 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 131-139, 2010;Published online in Wiley InterScience (***). DOI 10.1002/ima.20236
A low complexity M-channel multiple description coding scheme is developed in this paper, in which each description carries one subset of the input with a higher bit rate and the rest with a lower bit rate. The lower-...
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A low complexity M-channel multiple description coding scheme is developed in this paper, in which each description carries one subset of the input with a higher bit rate and the rest with a lower bit rate. The lower-rate codings in different descriptions are designed to be mutually refinable using staggered scalar quantizers. For correlated sources, a two-rate predictive coding is used in each description. Closed-form expressions of the distortions are derived when different numbers of descriptions are received. The application of the proposed scheme in lapped transform based image coding is also investigated, and the optimal transform is obtained. Experimental results using both 1-D memoryless sources and 2-D images demonstrate the superior performance of the proposed scheme.
In this paper, we introduce a new predictive image compression scheme that compresses an image by a set of parameters computed for individual blocks of different types. These parameters include the average and differe...
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ISBN:
(纸本)9780769539829
In this paper, we introduce a new predictive image compression scheme that compresses an image by a set of parameters computed for individual blocks of different types. These parameters include the average and difference of the representative intensities of an image block, together with the index of a pattern associated with the block visual activity. The block representative gray values are computed through a histogram analysis of the block residuals and a pattern matching technique is employed to find the best match for the block bit-pattern from a pre-defined pattern book. To further reduce the bit rate, a predictive technique selectively predicts the parameters based on the corresponding values in the neighboring blocks. The simulation results confirm that the proposed technique can provide a high compression ratio with acceptable image quality of the compressed images.
We describe design of a low-complexity lossless and near-lossless image compression system with random access, suitable for embedded memory compression applications. This system employs a block-based DPCM coder using ...
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ISBN:
(纸本)9780819482945
We describe design of a low-complexity lossless and near-lossless image compression system with random access, suitable for embedded memory compression applications. This system employs a block-based DPCM coder using variable-length encoding for the residual. As part of this design, we propose to use non-prefix ( one-to-one) codes for coding of residuals, and show that they offer improvements in compression performance compared to conventional techniques, such as Golomb-Rice and Huffman codes.
predictive coding eliminates redundancy due to correlations between the current and past signal samples, so that only the innovation, or prediction residual, needs to be encoded. However, the decoder may, in principle...
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ISBN:
(纸本)9781424442966
predictive coding eliminates redundancy due to correlations between the current and past signal samples, so that only the innovation, or prediction residual, needs to be encoded. However, the decoder may, in principle, also exploit correlations with future samples. Prior decoder enhancement work mainly applied a non-causal filter to smooth the regular decoder reconstruction. In this work we broaden the scope to pose the problem: Given an allowed decoding delay, what is the optimal decoding algorithm for predictively encoded sources? To exploit all information available to the decoder, the proposed algorithm recursively estimates conditional probability densities, given both past and available future information, and computes the optimal reconstruction via conditional expectation. We further derive a near-optimal low complexity approximation to the optimal decoder, which employs a time-invariant lookup table or codebook approach. Simulations indicate that the latter method closely approximates the optimal delayed decoder, and that both considerably outperform the competition.
Fast and small foot print lossless image compressors aiming at hyper-spectral sensor for the earth observation satellite have been developed. Since more than one hundred channels are required for hyper-spectral sensor...
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ISBN:
(纸本)9780819483874
Fast and small foot print lossless image compressors aiming at hyper-spectral sensor for the earth observation satellite have been developed. Since more than one hundred channels are required for hyper-spectral sensors on optical observation satellites, fast compression algorithm with small foot print implementation is essential for reducing encoder size and weight resulting in realizing light-weight and small-size sensor system. The image compression method should have low complexity in order to reduce size and weight of the sensor signal processing unit, power consumption and fabrication cost. coding efficiency and compression speed enables enlargement of the capacity of signal compression channels, which resulted in reducing signal compression channels onboard by multiplexing sensor signal channels into reduced number of compression channels. The employed method is based on FELICS1, which is hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we applied two-dimensional interpolation prediction and adaptive Golomb-Rice coding, which enables small footprint. It supports progressive decompression using resolution scaling, whilst still delivering superior performance as measured by speed and complexity. The small footprint circuitry is embedded into the hyper-spectral sensor data formatter. In consequence, lossless compression function has been added without additional size and weight.
In this paper, we deal with layered predictive compression of animated meshes represented by series of 3D static meshes with same connectivity. We propose two schemes to improve the prediction. First improvement is us...
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ISBN:
(纸本)9781424479948
In this paper, we deal with layered predictive compression of animated meshes represented by series of 3D static meshes with same connectivity. We propose two schemes to improve the prediction. First improvement is using weighted spatial prediction rather than averaging neighbor vertices. The second improvement is a novel predictor based on rotation angle of incident triangles in current and previous frames. The experimental results show that around 6- 10 % bitrate reduction can be achieved by replacing the spatial prediction in the reference coder with the proposed weighted spatial prediction and 9- 18 % bitrate reduction is possible with the proposed angle based predictor using weighted spatial prediction, depending on the content and quantization level.
This paper addresses the problem of joint decoding of stereo JPEG image pairs. Such images typically contain a high degree of redundancy. predictive coding could efficiently capture this redundancy, but cameras would ...
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ISBN:
(纸本)9781424479948
This paper addresses the problem of joint decoding of stereo JPEG image pairs. Such images typically contain a high degree of redundancy. predictive coding could efficiently capture this redundancy, but cameras would have to implement proprietary encoding solutions in this case as no such standard technology is available. We propose to rather use the popular JPEG compression tools in the cameras, and focus on the joint decoding problem for quality enhancement. We formulate this as a constrained optimization problem and show how regularization leads to more consistent results. It is similar to a distributed source coding framework, where the exploitation of the correlation at the decoder permits to save on the overall bandwidth. Experiments on natural stereo images show an improvement in both visual quality and PSNR when compared to separate decoding.
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