16523105
Region-based rate control and bit allocation for wireless video transmission
In this paper, we propose a joint source-channel region-based rate control algorithm for real-time video transmissions over wireless systems. During the video transmission, the channel throughput available to the video encoder in the wireless systems is inherently variable, due to the retransmission of the error packets using the automatic repeat request (ARQ) error control. The variable data rate of the wireless system is characterized by the packet-level Gilbert two-state Markov Model, the parameters of which are extracted from the statistical properties of the channel information obtained from the wireless channel simulator. The proposed algorithm adopts a fast but effective block-based segmentation method to extract the regions of interest. Unlike traditional bit allocation methods used in the region/content-based rate control, the algorithm exploits the most effective criteria "coding qualities" as quantitative factors to directly control bit allocation among different regions so as to achieve better visual quality in the regions of interest. The computational complexity of the algorithm is low making it suitable for real-time applications. Compared with the MPEG-4 rate control algorithm, our algorithm can effectively enhance the perceptual quality for the regions of interest and significantly reduce the number of frame skipping; thereby, improve the smoothness of the video.
47269670
Motion estimation for content adaptive video compression
A multistage motion estimation scheme is proposed. The scheme extracts video characteristics by first performing an online video analysis separately for foreground and background regions. Motion parameters are extracted and passed to the next stage. The next stage includes a mathematical model for the block distortion surface (BDS) that enables the algorithm to accordingly adjust its search technique. The search is performed on a precise search area adaptive to the statistical property of the motion vector prediction error. Due to its self-tuning property, not only does the proposed scheme adapt to scenes by yielding better visual quality but it also yields a lower computational complexity, compared with the other predictive motion estimation algorithms on standard benchmark sequences
12254119
Wireless network security
205906582
Polygonal approximation using genetic algorithms
A polygon approximation method based on genetic algorithms is proposed in this paper. In the method, a chromosome is used to represent a polygon and is represented by a binary string. Each bit, called a gene, represents a point on the object curve. The objective function is defined as the integral square error between the given curve and the approximated polygon. Three genetic operators namely selection, crossover and mutation, have been constructed for this specific problem. The proposed method when compared with three existing methods can obtain superior approximation results with less error norm with respect to the original curves.
9741409
VLSI Decoder Architecture for High Throughput, Variable Block-size and Multi-rate LDPC Codes
A low-density parity-check (LDPC) decoder architecture that supports variable block sizes and multiple code rates is presented. The proposed architecture is based on the structured quasi-cyclic (QC-LDPC) codes whose performance compares favorably with that of randomly constructed LDPC codes for short to moderate block sizes. The main contribution of this work is to address the variable block-size and multi-rate decoder hardware complexity that stems from the irregular LDPC codes. The overall decoder, which was synthesized, placed and routed on TSMC 0.13-micron CMOS technology with a core area of 4.5 square millimeters, supports variable code lengths from 360 to 4200 bits and multiple code rates between frac14 and 9/10. The average throughput can achieve 1 Gbps at 2.2 dB SNR.
8079300
Solving irregularly structured problems based on distributed object model
This paper presents a distributed object model called MOIDE (multi-threading object-oriented infrastructure on distributed environment) for solving irregularly structured problems. The model creates an adaptive computing infrastructure for developing and executing irregular applications on distributed systems. The infrastructure allows dynamic reconfiguration to match the evolution of irregular computation and available system resources. A unified communication mechanism is built to integrate different communication paths on heterogeneous systems to support efficient communication. Autonomous load scheduling approach is proposed for dynamic load balancing. A runtime system is developed to implement MOIDE-based computing. Applications including N-body problem, ray tracing, and conjugate gradient are developed to demonstrate the advantages of the model.
15422371
Priority assessment of software requirements from multiple perspectives
The development of complex software systems involves collecting software requirements from various stakeholders. Often stakeholder perceptions conflict during the requirements elicitation phase. An effective technique to resolve such a conflict is needed. We presented a framework that prioritizes software requirements gathered from multiple stakeholders by incorporating inter-perspective relationships, which is not addressed by existing priority assessment techniques. We use a relationship matrix to analyze the impact between requirements and facilitate the integration process which assesses their priorities based on their relationships from multiple perspectives. It allows the development team to resolve conflicts effectively and concentrate their valuable time and resources on the critical few requirements from multiple perspectives that directly contribute to high customer satisfaction.