We propose a novel approach for light field compression that incorporates disparity compensation into 4-D wavelet coding using disparity-compensated lifting. With this approach, we obtain the benefits of wavelet codin...
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We propose a novel approach for light field compression that incorporates disparity compensation into 4-D wavelet coding using disparity-compensated lifting. With this approach, we obtain the benefits of wavelet coding, including compression efficiency and scalability in all dimensions. Additionally, our proposed approach solves the irreversibility limitations of previous wavelet coding approaches. Experimental results show that the compression efficiency of the proposed technique outperforms current state-of-the-art wavelet coding techniques by a wide margin.
Very sparse bitmaps are used in a wide variety of applications, ranging from adjacency matrices in representation of large sparse graphs, representation of sparse space occupancy to book-keeping in databases. A method...
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Very sparse bitmaps are used in a wide variety of applications, ranging from adjacency matrices in representation of large sparse graphs, representation of sparse space occupancy to book-keeping in databases. A method based on pruning of the binary space partition (BSP) tree in the minimal description length (MDL) principle for coding very sparse bitmaps was proposed. This new method for coding of sparse bitmaps meets seemingly competing objectives of good compression, the ability of conducting queries directly in the compression domain, and simple and fast decoding.
A new video coding paradigm (PRISM) built on distributed coding principles has recently been proposed in R. Puri and K. Ramchandran, (2002, 2003). The PRISM framework rests heavily on channel coding concepts. The basi...
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A new video coding paradigm (PRISM) built on distributed coding principles has recently been proposed in R. Puri and K. Ramchandran, (2002, 2003). The PRISM framework rests heavily on channel coding concepts. The basic idea is to do intra-frame coding but to approach the coding efficiency of motion-compensated inter-frame coding by using channel codes to derive a coding rate rebate by "exploiting" the correlated side-information present in the form of previous temporal frames at the decoder. The coding strategy described in R. Puri and K. Ramchandran, (2002, 2003) was limited to rate-1/2 trellis coset codes, which limit the granularity at which the correlated side-information can be exploited. In this work, we generalize the coset coding framework to multi-level codes which allow more flexible encoding rates and the capability to exploit correlations with much finer granularity. Simulation results validate the better compression performance (of the order of 1 dB for typical tests) of the multilevel framework.
Multiple Description (MD) coding of predictively coded sources is of practical interest in several multimedia applications such as redundant storage of video/audio data, and real-time video/audio telephony. A key prob...
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ISBN:
(纸本)0780375106
Multiple Description (MD) coding of predictively coded sources is of practical interest in several multimedia applications such as redundant storage of video/audio data, and real-time video/audio telephony. A key problem associated with predictive MD coding is the occurrence of predictive mismatch. In the present paper, we pose the problem of predictive MD coding as a variant of the Wyner-Ziv decoder side-in formation problem. We propose an approach based on the use of coset codes for predictive MD coding, which avoids predictive mismatch without requiring restrictive channel assumptions or high latency. We specifically consider two-channel predictive MD coding of a first-order Gauss-Markov process. Results indicate that the proposed approach significantly out-performs alternative approaches in terms of rate-distortion performance.
Data implying that neurons can communicate with synchronous volleys are difficult to reconcile with the bulk of single unit recordings which do not show synchrony yet reveal substantial correlations with animal behavi...
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Data implying that neurons can communicate with synchronous volleys are difficult to reconcile with the bulk of single unit recordings which do not show synchrony yet reveal substantial correlations with animal behavior. Our simulations reconcile these two sets of results by sharing a synchronous signal among groups of neurons in a way that the average signal through any particular neuron exhibits conventional receptive field properties. The simulation models a subset of the connections between the LGN and VI and shows that synchronous computation at a high firing rate can appear at an individual cell as random spikes at a lower rate. (C) 2002 Elsevier Science B.V. All rights reserved.
Among a context of three pixels, the present JPEG-LS produces predicted values based on whether a vertical edge or a horizontal edge is detected. When a diagonal edge exists, however, experiments and observation revea...
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Among a context of three pixels, the present JPEG-LS produces predicted values based on whether a vertical edge or a horizontal edge is detected. When a diagonal edge exists, however, experiments and observation reveal that such a prediction will generate large predictive errors. By applying the triangle inequality to the analysis of predictive templates in JPEG-LS, we propose a diagonal-edge detection scheme to reduce the predictive error and hence provide an improvement on the prediction accuracy. Experiments are carried out to test the proposed scheme for a group of sample images. In comparison with the current JPEG-LS prediction, our scheme produces lower prediction errors, in terms of both MSE measurement and visual comparison of error images. (C) 2002 Society of Photo-Optical Instrumentation Engineers.
作者：
Friston, KJUCL
Wellcome Dept Cognit Neurol London WC1N 3BG England
Unsupervised models of how the brain identifies and categorizes the causes of its sensory input can be divided into two classes: those that minimize the mutual information (i.e., redundancy) among evoked responses and...
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Unsupervised models of how the brain identifies and categorizes the causes of its sensory input can be divided into two classes: those that minimize the mutual information (i.e., redundancy) among evoked responses and those that minimize the prediction error. Although these models have the same goal, the way that goal is attained, and the functional architectures required, are fundamentally different. This review describes the differences, in the functional anatomy of sensory cortical hierarchies, implied by the two models. We then consider how neuroimaging can be used to disambiguate between them. The key distinction reduces to whether backward connections are employed by the brain to generate a prediction of sensory inputs. To ascertain whether backward influences are evident empirically requires a characterization of functional integration among brain systems. This review summarizes the approaches to measuring functional integration in terms of effective connectivity and proceeds to address the question posed by the theoretical considerations. In short, it will be shown that the conjoint manipulation of bottom-up and top-down inputs to an area can be used to test for interactions between them, in elaborating cortical responses. The conclusion, from these sorts of neuroimaging studies, points to the prevalence of top-down influences and the plausibility of generative models of sensory brain function.
The volumetric data set is important in many scientific and biomedical fields. Since such sets may be extremely large, a compression method is critical to store and transmit them. To achieve a high compression rate, m...
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ISBN:
(纸本)0819447145
The volumetric data set is important in many scientific and biomedical fields. Since such sets may be extremely large, a compression method is critical to store and transmit them. To achieve a high compression rate, most of the existing volume compression methods are lossy, which is usually unacceptable in biomedical applications. We developed a new context-based non-linear prediction method to preprocess the volume data set in order to effectively lower the prediction entropy. The prediction error is further encoded using Huffman code. Unlike the conventional methods, the volume is divided into cubical blocks to take advantage of the data's spatial locality. Instead of building one Huffman tree for each block, we developed a novel binning algorithm that build a Huffman tree for each group (bin) of blocks. Combining all the effects above, we achieved an excellent compression rate compared to other lossless volume compression methods. In addition, an auxiliary data structure, Scalable Hyperspace File (SHSF) is used to index the huge volume so that we can obtain many other benefits including parallel construction, on-the-fly accessing of compressed data without global decompression, fast previewing, efficient background compressing, and scalability etc.
JPEG-LS is the latest pixel based lossless to near lossless still image coding standard introduced by the Joint Photographic Experts Group (JPEG) (1). In this standard simple localized edge detection techniques are us...
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ISBN:
(纸本)0819444111
JPEG-LS is the latest pixel based lossless to near lossless still image coding standard introduced by the Joint Photographic Experts Group (JPEG) (1). In this standard simple localized edge detection techniques are used in order to determine the predictive value of each pixel. These edge detection techniques only detect horizontal and vertical edges and the corresponding predictors have only been optimized for the accurate prediction of pixels in the locality of horizontal and/or vertical edges. As a result JPEG-LS produces large prediction errors in the locality of diagonal edges. In this paper we propose a low complexity, low cost technique that accurately detects diagonal edges and predicts the value of pixels to be encoded based on the gradients available within the standard predictive template of JPEG-LS. We provide experimental results to show that the proposed technique outperforms JPEG-LS in terms of predicted mean squared error, by a margin of up to 8.51%.
The block-based fast transmission scheme, which is a typical stored video delivery scheme, is reasonable in terms of its bandwidth efficiency. However, it causes packet loss because of its burst data transmission meth...
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The block-based fast transmission scheme, which is a typical stored video delivery scheme, is reasonable in terms of its bandwidth efficiency. However, it causes packet loss because of its burst data transmission method. Thus, we suggest a slotted multicast scheme for MPEG video based on the block transmission scheme to maintain a higher quality and to include time constraints. We define two delivery units, the "GoPs group" and the "frame type", on the basis of the MPEG characteristics with periodical NACK feedback from the clients. The former is tolerant to burst packet loss, and the latter gives priority to important frames. Block multicast has two phases: a "transmission phase" and a "retransmission phase". In the former, a server multicasts a block, and in the latter, a server retransmits lost packets using multicast according to the proper delivery unit.
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