Sharif Digital Repository

A novel burst correction coding for correction of bulk errors in block-based image coding is developed. The algorithm makes artificial correlation between image pixels that distorts the image. By choosing appropriate parameters, one can control this distortion to lie in acceptable ranges. Our method can exactly correct an erroneously decoded block when using lossless codecs. In the presence of lossy codecs, the algorithm encounters a processing error which makes a noisy image after correction. The Wiener filter is used to reduce this noise. Experimental results show that our method can correct corrupted large blocks in images; the ability that other previously reported approaches have not... 

A new high-performance architecture for decoding the irregular Low-Density Parity-Check (LDPC) codes with respect to the iterative message-passing decoding algorithm is explored. The proposed method is based on reducing the logic delays in the iterative processing of the bit nodes and check nodes leading to the increment of maximum possible frequency. The simulations show the efficiency of the proposed method in low/high-complexity graph matrices, though it is more effective in high-complexity ones. About 28% reduction of the combinational delay in the bit/check processors is explored without much impacting the area consumption. ©2007 IEEE  

Mesh-based motion estimation is an important tool for video coding especially with low bit rate. In this paper, a new method for interpolating pixel motion from adjacent mesh nodes with the ability of omitting independent nodes is proposed. By exploiting fuzzy rules to determine the association of pixel and neighboring nodes, the proposed interpolation can detach pixels from some nodes. Consequently, it can deal with those critical patches on objects boundary which their nodes do not belong to one object. Updating the membership functions of each rule with specified strategy makes the interpolation adaptive with non-stationary conditions of image sequences and decreases sensitivity to... 

Motion estimation and compensation is an essential part of existing video coding systems. Compared to the widely used block-matching algorithms (BMA), the mesh-based motion estimation (MME) produces better subjective and objective qualified image sequences in many cases, especially at low bitrates. However, the iterative refinement step of the MME is computationally too expensive. In this paper, we propose a fast MME scheme, which adjusts its interpolation patterns to the motion features of image sequences to achieve higher quality reconstructed results. Experimental results show notable rate-distortion improvement over both the BMA and the conventional non-iterative MME schemes, especially... 

Recent studies have demonstrated that high-level semantics in data can be captured using sparse representation. In this paper, we propose an approach to human body pose estimation in static images based on sparse representation. Given a visual input, the objective is to estimate 3D human body pose using feature space information and geometrical information of the pose space. On the assumption that each data point and its neighbors are likely to reside on a locally linear patch of the underlying manifold, our method learns the sparse representation of the new input using both feature and pose space information and then estimates the corresponding 3D pose by a linear combination of the bases... 

In this work, we study the lossy source coding of a Gaussian source with polar codes. We show through two distributions on discrete alphabet, quantized approach as well as Central Limit Theorem (CLT) approach, when the alphabet size grows to infinity, polar codes can achieve the rate distortion bound for a Gaussian source. By comparing the rate of convergence on two distributions, we show that the quantized approach have a better convergence rate than the CLT approach  

In this paper, a method for fast processing of data stream tuples in parallel execution of continuous queries over a multiprocessing environment is proposed. A copy of the query plan is assigned to each of processing units in the multiprocessing environment. Dynamic and continuous routing of input data stream tuples among the graph constructed by these copies (called the QueryMega Graph) for each input tuple determines that, after getting processed by each processing unit (e.g., processor), to which next processor it should be forwarded. Selection of the proper next processor is performed such that the destination processor imposes the minimum tuple latency to the corresponding tuple, among... 

In this paper we study the sum modulo two problem proposed by Körner and Marton. In this source coding problem, two transmitters who observe binary sources X and Y, send messages of limited rate to a receiver whose goal is to compute the sum modulo of X and Y. This problem has been solved for the two special cases of independent and symmetric sources. In both of these cases, the rate pair (H(X|Y), H(Y|X)) is achievable. The best known outer bound for this problem is a conventional cut-set bound, and the best known inner bound is derived by Ahlswede and Han using a combination of Slepian-Wolf and Körner-Marton's coding schemes. In this paper, we propose a new outer bound which is strictly... 

In this paper, we consider Causal Cognitive Interference Channel (CC-IFC), wherein the cognitive user overhears the channel and exploits knowledge of the primary user's message from the causally received signals. We propose a coding scheme which combines Compress-and-Forward (CF) strategy with Marton coding with common information at the cognitive user. Rate splitting for messages at both transmitters is used to have a collaborative strategy. Moreover, the cognitive user compresses its channel observation using Wyner-Ziv coding and splits the index of its compressed signal. Then, the cognitive user having common information to both receivers and private information to each of them, jointly... 

In recent years, enterprise Solid-State Drives (SSDs) are used in the caching layer of high-performance servers to close the growing performance gap between processing units and storage subsystem. SSD-based I/O caching is typically not effective in workloads with burst accesses in which the caching layer itself becomes the performance bottleneck because of the large number of accesses. Existing I/O cache architectures mainly focus on maximizing the cache hit ratio while they neglect the average queue time of accesses. Previous studies suggested bypassing the cache when burst accesses are identified. These schemes, however, are not applicable to a general cache configuration and also result... 

Transmission of video over error prone and still bandwidth limited wireless channels demand high compression efficiency and resilience to packet losses and errors. Scalable or layered video coding applied to highly compression efficient codecs is an ideal solution to the problem. However, scalability reduces compression efficiency of the coders. In this paper we show how compression efficiency of two-layer SNR scalable video coders can be retained via joint base-enhancement layer optimization. Simulation results show that joint base-enhancement layer optimization significantly outperforms separate optimization of the layers, and it closely follows the compression performance of the... 

A matrix pseudo inversion based method is developed for coding of images in real field in a way that at the receiver, one can restore the lost portions of the images. The proposed solution is similar to channel coding techniques, but it is done before source coding at the transmitter and after decoding of the compressed data at the receiver. Experiments show the effectiveness of the proposed solution in recove ring missed portions of the images and video frames. ©2007 IEEE  

A novel error resilient source coding method is proposed for video codecs such as H.264 standard. The main idea is to develop an error resilient part similar to the channel coders at the source coder. This enables the receiver to recover a damaged slice of a frame, inter or intra coded, up to a certain size determined by the encoder. In contrast to another previously approach presented in the literature, our algorithm has significantly less artifacts on the video frames with a considerable increase in speed  

An extended version of Lagrange interpolation is developed for coding of images in real field in a way that at the receiver, one can restore the lost portions of the images. The proposed solution is similar to channel coding techniques, but it is done before source coding at the transmitter and after decoding of the compressed data at the receiver. Our proposed solution is faster than the other one reported in the literature when the size of damaged blocks is large  

Video transcoding comprises the necessary operations for the conversion of a compressed video stream from one syntax to another one for inter-network communications, without the need of any further decoding and re-encoding process. The two most recent and popular standard video coders are H.263 and H.264. In this paper, we present tools to enable low complexity intra transcoding from H.263 to H.264 using a novel fast intra prediction mode decision algorithm that does not require extra computation. It is shown that due to basic similarities of H.263 and H.264 it is possible to reuse predictor side information, so this side information is used to simplify the mode and direction decision for... 

Within the compressive sensing (CS) framework, one effective way to increase the likelihood of successful signal reconstruction is to employ random processes in the construction of the sensing matrix. This study presents a 3D holey cavity, with diverse frequency modes, to spectrally code, that is, randomize, the ultrasound wave fields. The simulated results show that the use of such a cavity enables imaging simple or complex targets, such as spheres or the letter E, by only a single transceiver—something that is not possible without the use of a coding structure like the cavity. The effect of noise on imaging results and the size of the targets on the first-order Born approximation (BA) are... 

We study learning algorithms when there is a mismatch between the distributions of the training and test datasets of a learning algorithm. The effect of this mismatch on the generalization error and model misspecification are quantified. Moreover, we provide a connection between the generalization error and the rate-distortion theory, which allows one to utilize bounds from the rate-distortion theory to derive new bounds on the generalization error and vice versa. In particular, the rate-distortion-based bound strictly improves over the earlier bound by Xu and Raginsky even when there is no mismatch. We also discuss how 'auxiliary loss functions' can be utilized to obtain upper bounds on the... 

This paper proposes two enhanced cross-diamond-hexagonal search algorithms to solve the motion-estimation problem in video coding. These algorithms differ from each other by their second step search only, and both of them employ cross-shaped pattern in first step. Proposed method is an improvement over CDHS, eliminating some checking points of CDHS algorithm. Experimental results show that the proposed methods perform faster than the diamond search (DS) and CDHS, whereas similar quality is preserved. © 2005 IEEE  

A hybrid video codec, where the intraframe pictures are wavelet-based coded and the interframe pictures are coded with a standard H.263 codec is proposed. We show that intraframe-wavelet coded pictures not only improve the quality of I-pictures but also result in lower distorted prediction pictures that outperforms a pure H.263 video codec. © 2005 IEEE  

Power and bandwidth constraints are two major challenges in wireless sensor networks. Since a considerable amount of energy in sensor networks is consumed for data transmission, compression techniques may prolong the life of such networks. Moreover, with fewer bits to transmit, the network can cope better with the problem of inadequate bandwidth. In this paper, we consider an image sensor network and propose a paradigm based on the principles of Distributed Source Coding (DSC) for efficient compression. Our method relies on high correlation between the sensor nodes. The algorithm consists of two phases: the Training Phase and the Main Phase. In the Training Phase an aggregation node or a...