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In this paper, a novel frame-level dependent bit allocation (DBA) method is proposed. Our contribution is two-fold: First, the dependency between adjacent frames is quantitatively measured by the introduced inter-frame dependency model(IFDM). The IFDM not only holds for slow video sequences, but remains valid for video sequences of median and high motion as well. Second, based on the IFDM, the conventional...
A time-multiplexed row-parallel architecture is proposed for the real-time implementation of bivariate algebraic integer (AI) encoded 2-D discrete cosine transform (DCT) of images and video sequences. The architecture is based on the Arai algorithm with AI encoding. This leads to an 8×8 2-D DCT which is entirely free of quantization errors. The error free coefficients may be converted into a regular...
The aim of compressed sensing is to recover attributes of sparse signals using very few measurements. Given an overall bit budget for quantization, this paper demonstrates that there is value to redundant measurement. The measurement matrices considered here are required to have the property that signal recovery is still possible even after dropping certain subsets of D measurements. It introduces...
Biometric secret-key binding inherently requires signal processing and error correction schemes due to noisy measurement readings. Two previously proposed strategies, Quantization Index Modulation (QIM) andWyner-Ziv (WZ) coding, are studied in the context of biometric key binding. We characterize the tradeoff between key rateleakage and key rate-reconstruction distortion, showing that while WZ coding...
In order to obtain consecutive and smooth video encoding quality under the network bandwith and delay constrained, an optimal rate control algorithm was presented. Because the linear MAD prediction of the basic unit costs too many operations and exists deviation, in this paper, we present a new weighted mode for prediction, and more, macroblock layer rate control is added in the algorithm. Simulation...
Without changing the features of the integer DCT transform radix, improve on its matrix filling rules and get a new type of integer DCT transform radix. Other than orthogonality, such a variety of integer DCT transform radix also meet the quantity relationships between elements of an integer as a matrix, and the normalized coefficients matrix have similar characteristic with the original DCT matrix...
This paper presents a network-adaptive multiple description coding (MDC) method for enhanced video streaming over multipath channels. The novel feature of the proposed MDC network adaptation scheme is the generation of a controlled amount of side information to compensate for drift distortion due to packet loss. This yields higher robustness of multiple description (MD) H.264/AVC streams than single...
The H.264 encoder has input parameters that determine the bit rate and distortion of the compressed video and the encoding complexity. These encoding parameters may significantly affect not only the encoding performance, but also affect the cross-layer design optimization for the video streaming transmission over wireless networks. However, it is very difficult to derive the impact factors of these...
We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex, yielding precise characterization in the high-rate regime. Our main contribution is a simple and asymptotically optimal algorithm for solving this problem. Performance...
We propose a new method for modeling the temporal correlation in videos, based on local transforms realized by Lie group operators. A large class of transforms can be theoretically described by these operators, however, we propose to learn from natural movies a subset of transforms that are statistically relevant for video representation. The proposed transformation modeling is further exploited to...
Summary form only given. Existing distortion measurements for the B-spline-based shape coding include ap proximation, quantization, or parameterization process, so they are approximate techniques. They may inaccurately predict the actual distortion value, which motivates us to construct a model that can accurately measure the actual distortion. It was reported that the actual distortion for reconstruction...
Quantizers for probabilistic sources are usually optimized for mean-squared error. In many applications, maintaining low relative error is a more suitable objective. This measure has previously been heuristically connected with the use of logarithmic companding in perceptual coding. We derive optimal companding quantizers for fixed rate and variable rate under high-resolution assumptions. The analysis...
To the condition of the complexity of AVS-M transforming quantization all-zero block detection algorithm changes with video content changes, according to the characteristics of adjacent video frame contents have dependence, a adaptive complexity control algorithm for AVSM transforming quantization is proposed. According to reasonable parameter choice, the algorithm can converge to the given computational...
This paper introduces an adaptive scanning order for bitplane image coding engines, which is devised from a rate-distortion optimization perspective that uses recent advances in coefficient modeling and distortion estimation. The main idea is to always select the next coefficient to be coded so that image distortion and code stream length are minimized. The sequence of visited coefficients is adapted...
Compressive sensing (CS) is recently and enthusiastically promoted as a joint sampling and compression approach. The advantages of CS over conventional signal compression techniques are architectural: the CS encoder is made signal independent and computationally inexpensive by shifting the bulk of system complexity to the decoder. While these properties of CS allow signal acquisition and communication...
We consider a class of distributed algorithms for computing arithmetic averages (average consensus) over networks of agents connected through digital noisy broadcast channels. Our algorithms combine error-correcting codes with the classical linear consensus iterative algorithm, and do not require the agents to have knowledge of the global network structure. We improve the performance by introducing...
The problem of compressing a real-valued sparse source using compressive sensing techniques is studied. The rate distortion optimality of a coding scheme in which compressively sensed signals are quantized and then reconstructed is established when the reconstruction is also required to be sparse. The result holds in general when the distortion constraint is on the expected p-norm of error between...
A new coding scheme for image transmission over noisy channel is proposed. Similar to standard image compression, the scheme includes a linear transform followed by embedded scalar quantization. Joint source-channel coding is implemented by optimizing the rate allocation across the source subbands, treated as the components of a parallel source model. The quantized transform coefficients are linearly...
This paper addresses coding for power transfer, modulation, and error control for the reader-to-tag channel in near-field passive radio frequency identification (RFID) systems using inductive coupling as a power transfer mechanism. Different assumptions on channel noise (including two different models for bit-shifts, insertions and deletions, and additive white Gaussian noise) are discussed. In particular,...
Real-time video compression applications such as Digital Video Camera (DVC), Television Studio Broadcast, and Surveillance video utilize the H.264/AVC video encoder in intra-only encoding mode. The H.264/AVC standard supports multiple intra-prediction modes to reduce spatial redundancy in the video frame. The intra-prediction process for a current pixels block requires the reconstructed pixels from...
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