An optical data processing and communication system provides enormous potential bandwidth and a very high processing speed, and it can fulfill the demands of the present generation. For an optical computing system, several data processing units that work in the optical domain are essential. Memory elements are undoubtedly essential to storing any information. Optical flip-flops can store one bit of optical information. From these flip-flop registers, counters can be developed. Here, the authors proposed an optical master-slave (MS)-JK flip-flop with the help of two-input and three-input optical NAND gates. Optical NAND gates have been developed using semiconductor optical amplifiers (SOAs). The nonlinear polarization switching property of an SOA has been exploited here, and it acts as a polarization switch in the proposed scheme. A frequency encoding technique is adopted for representing data. A specific frequency of an optical signal represents a binary data bit. This technique of data representation is helpful because frequency is the fundamental property of a signal, and it remains unaltered during reflection, refraction, absorption, etc. throughout the data propagation. The simulated results enhance the admissibility of the scheme.
We propose an efficient technique for temporally aligning video sequences of similar activities. The proposed technique is able to synchronize view-variance videos from different scenes performing similar 3-D activities. Unlike existing techniques that just consider unidirectional alignment, the proposed technique considers symmetric temporal alignment and computes the optimal alignment by eliminating any view-based bias. The advantages of our technique are validated by experiments conducted on synthetic and real video data. The experimental results show that the proposed technique out-performs existing techniques in several test video sequences.
Forward error correction (FEC) improves the quality of compressed video transmitted through a lossy network for real-time applications such as video streaming. The FEC techniques are generally applied on source video packets at the frame level. In this paper, we propose a technique where the FEC is applied on source packets at the group-of-pictures (GoP) level assuming an MPEG-like compression scheme. We derive analytically an estimate of the average playable frame rate for a given packet loss probability. Our analysis over a range of network conditions indicates that in most practical network conditions, the proposed technique provides a larger playable frame rate compared to the frame-level FEC technique. This analysis results are also validated by video streaming simulations conducted on the NS-2 network simulator.
With the increased emphasis on security and personal authentication, an accurate biometric-based authentication system
has become a critical requirement in a variety of applications. Among different biometrics, authentication based on iris
features has received a lot of attention since its introduction in 1992. The wavelet transform has been proposed by
several researchers for extracting iris features for authentication. Although classical wavelets provide a good
performance, they suffer from limited orientation selectivity. In this paper, we investigate the potentials of using the
contourlet transform to represent the iris texture. A new iris representation and matching system based on contourlet
transform is proposed. The contourlet transform not only shares the multiscale and localization properties of wavelets,
but also has a higher degree of directionality and anisotropy. The proposed matching system is experimented in both
verification and identification modes. Results have shown the significance of the new technique, especially in case of
low quality iris images and highly security demanding applications.
We present a robust and computational low complex method to estimate the physical camera parameters, intrinsic and extrinsic, for scene shots captured by cameras applying pan, tilt, rotation, and zoom. These parameters are then used to split a sequence of frames into several subsequences in an optimal way to generate multiple sprites. Hereby, optimal means a minimal usage of memory while keeping or even improving the reconstruction quality of the scene background. Since wide angles between two frames of a scene shot cause geometrical distortions using a perspective mapping it is necessary to part the shot into several subsequences. In our approach it is not mandatory that all frames of a subsequence are adjacent frames in the original scene. Furthermore the angle-based classification allows frame reordering and makes our approach very powerful.
We present a technique to robustly transmit regions of interest in the JPEG2000 framework. The technique assumes a prioritized region of interest coding and optimally assigns channel protection to the coded data according to the importance of every packet in the final bit stream. The mean energy of the transform coefficients contained in a packet, and the distance of a packet from the region of interest, determine the importance of every packet. Channel protection is achieved by means of a concatenation of a cyclic redundancy check outer coder and an inner rate-compatible convolutional coder. Simulation results performed over a Rayleigh-fading channel show an improvement in the visual quality of the reconstructed images.
The use of multimedia data is growing at a rapid rate, and bringing multimedia services to terminals with limited capabilities is a major challenge. Efficient schemes are hence required for adapating the multimedia content for delivery to devices with limited resources. In the conventional server and proxy-based architectures, the adaptation is performed either at the server or at the proxy resulting in the loading of the server and the proxy. In this paper we propose a novel distributed adaptation architecture suitable for resource-limited multimedia terminals as well as wired connections with high bandwidths. Here, the data can be adapted at the proxy or at the server, resulting in a faster adaptation process. In addition, we propose an efficient cache replacement policy at the proxy. The proposed architecture is very flexible for both mobile and wired networks. The experimental results show that the proposed architecture improves the performance of the proxy and the server, and reduces network congestion and latency.
Recently established high definition television (HDTV) standard is expected to replace the conventional analog television standards such as NTSC, PAL and SECAM in the next few years. However the high cost of HDTV is proving to be a major factor impeding its popularity. Integrating HDTV with other home appliances is likely to increase its usefulness and popularity. In this paper, we propose an efficient scheme to use HDTV as a computer monitor in addition to its entertainment role. In the proposed scheme, we assume that the main computer is situated in a remote location. The computer raster in the remote server is compressed using an MPEG-2 encoder and transmitted to the home. The built in MPEG-2 decoder in HDTV decompresses the bit stream, and displays the raster. The HDTV will be fitted with a mouse and keyboard, through which the interaction with the remote computer server can be performed. The HDTV can thus be used as a high-resolution computer terminal. The experimental results show that the performance of HDTV as a remote terminal is very good, with marginal degradation in text quality due to compression noise.
We propose two modi ed versions of the original wavelet di erence reduction (WDR) algorithm proposed by Tian and Wells. The rst algorithm encodes an image without entropy coding and achieves comparable PSNR performance with the original WDR at low bit rate while exceeding the PSNR performance of original WDR algorithm at medium to high bitrates. The second algorithm achieves slightly higher PSNR performance than that of original WDR with similar computational complexity. The modification to the original WDR is based on the observation that encoding the symbol streams generated in the sorting pass (significance map) and re nement pass (magnitudes) separately can be beneficial. We can either encode the symbol streams under different contexts using entropy coder, or output the raw symbol streams without entropy coding stage. It is shown in the experiments that up to 1/3 of both the encoding time and the decoding time can be saved without sacrificing any PSNR performance when compared to the original WDR.
The growth of the Internet and the World Wide Web has created an enormous demand for wideband data distribution around the globe. Satellite networks provide global reach and wide area coverage, especially to remote, rural and inaccessible regions. With a limited bandwidth, congestion is likely to occur when the demand for the bandwidth is high. In this paper, we present a capacity and flow assignment (CFA) model for the satellite ATM networks. We then present a stochastic programming approach to optimize the CFA in the satellite networks. The proposed model has been evaluated with a prototype network with 4 nodes, and the simulation results are promising.
The traffic control is a critical issue in ATM networks. In ATM, the traffic control is implemented at different levels: cell level, call level and network flow level. The virtual path (VP) distribution involves both call level and flow level controls. The VP distribution is a logic network design problem based on the physical network. Several VP optimization schemes have been proposed, and a large number of these schemes are based on the flow assignment (FA) model. In this paper, an improved flow model is proposed with a non-linear objective function. The proposed model incorporates two concepts: VP capacity and VP flow, to perform the optimization. The proposed model distributes traffic on all available VPs evenly, and has redundant capacities. Hence, the resulting VP system is resilient to input traffic changes and physical link failures. In addition to the proposed FA model, we introduce a stochastic programming (SP) methodology to allocate virtual paths when the incoming traffic changes stochastically. Experimental results show that the proposed flow model and the stochastic methodology improve the performance of ATM networks.
The World Wide Web has become an essential tool as well as an entertainment medium in our daily life. However, efficient web browsing from anywhere at anytime, presents an opportunity as well as a challenge to the web document authors. The mobile users have a totally different requirement compared to the conventional wired users. The mobile networks have limited bandwidths, and the mobile terminals have limited resolutions. Hence a scheme is needed to adapt the web-data and multimedia contents such that they can be used on devices with limited resources such as bandwidth, resolution and memory space. In this paper we propose a novel mobile proxy server architecture suitable resource-limited multimedia terminals. Here, a distributed method is employed to adapt the multimedia data such that the adaptation is neither fully based on the proxy server nor fully based on the web server. Adaptation process is expected to be faster since the data adaptation loads are distributed between the proxy and the web server. Simulation results suggest that a significant performance improvement can be achieved with the proposed architecture.
The application of images and video has increased significantly in recent years. It is crucial to develop indexing techniques for searching images and video based on their content. Recently, several indexing techniques have been proposed in both pixel and compressed domain. Due to its lower computational complexity, compressed domain indexing techniques are becoming popular. Among the compression techniques, discrete-wavelet-transform based techniques have become popular because of its excellent energy compaction and multi-resolution capability. The upcoming JPEG2000 image compression standard is also based on a wavelet coder. In this paper, a progressive bit-plane indexing scheme in the JPEG2000 framework is proposed. Here, a 2D significant0bit- map array and a 2D histogram of significant bits of wavelet coefficients are used as the image indices. Image retrieval is performed by matching the index of the query and candidate images from the database. Experimental results show that the proposed scheme provides a good indexing performance.
Automatic video indexing is an important feature in video database applications. Several techniques have appeared in recent literature for detecting object motion and camera operations present in a video. However, most of these techniques operate in the spatial domain. Since, video is likely to be stored in compressed form, it is crucial to deep detection techniques which can operate on the compressed data. Wavelet transform has recently emerged as a powerful tool for efficient compression and indexing. In this paper, we present a technique for temporal indexing using multiresolution motion vectors in a wavelet framework. We note that several approaches for indexing the spatial content of video have already been proposed in the literature. A combination of spatial and temporal indices constitutes a spatio-temporal index of video in the wavelet domain.
Automatic video indexing is an important feature in the design of a video databases. Recently, compressed domain techniques have become popular due their inherent advantages of efficiency and reduced complexity. Wavelet transform is emerging as a powerful tool for efficient compression of visual information. A variety of wavelet based video compression techniques have been reported in the literature. However, there has been little work done in the area of video indexing in the wavelet domain. In this paper, we present video segmentation techniques in a wavelet based compression framework. These techniques employ wavelet coefficients, their distribution, and the motion vectors estimated by the associated video coder. Simulation result shows that the proposed techniques provide a good indexing performance at a low complexity.
Wavelet transform is an important tool for image and video coding applications. Several motion estimation techniques have been proposed in the wavelet domain. The coarse-to-fine motion estimation techniques generally have a lower complexity at the expense of inaccurate estimation. On the other hand, the fine-to-coarse motion estimation techniques provide a superior estimation, but at a higher complexity. In this paper, we propose an efficient video coder in the wavelet domain. First, we propose an adaptive resolution selection for motion estimation where a lowpass subband at an appropriate scale is employed for coarse motion estimation. The motion vectors of subbands from higher/lower resolutions are then predicted from the coarse motion vectors and are further refined using a small search window. Secondly, we propose an adaptive bit allocation technique where the bits are allocated optimally between the motion vectors and the displaced frame difference. This is performed by minimizing a cost function based on the Lagrange multiplier method. Simulation result shows that the proposed video coder provides a superior coding performance compared to other multi-resolution techniques proposed in the literature.
Image and video indexing techniques are crucial in multimedia applications. A number of the indexing techniques which operate in the pixel domain have been reported in the literature. The advent of compression standards has led to the proliferation of indexing techniques in the compressed domain. In this paper, we present a critical review of the compressed domain indexing techniques proposed in the literature. These include transform domain techniques using Fourier transform, cosine transform, Karhunen-Loeve transform, subbands and wavelets; and spatial domain techniques using vector quantization. In addition, temporal indexing techniques using motion vectors are also discussed.
Histogram comparison is a popular technique for image indexing. Given a query image, histogram-based techniques can retrieve similar images from a database, which were acquired under similar illumination levels. However, these techniques fail when images are acquired under different illumination conditions. In this paper, we propose two novel histogram-based techniques which are robust to the changes in illumination. First, we propose to employ moments of the image histogram which are invariant to translation and scaling of image gray levels. Secondly, we propose to compare the parameters of histograms of the wavelet subbands for indexing. These parameters are modified appropriately to counter the effect of changes in illumination. The proposed techniques are computationally inexpensive and can be easily integrated within a wavelet-based image coder.
Wavelet transform has been proven to be a valuable tool for image and video coding applications. Recently, a multiresolution motion estimation (MRME) technique has been proposed for wavelet-based video compression. The MRME technique estimates the motion vector hierarchically from the low resolution to the high resolution wavelet subimages, thereby reducing the computational complexity. In this paper, we propose two techniques to enhance the coding performance of the baseline MRME technique. First, we propose to use an adaptive threshold to determine whether a motion vector should be sent to the receiver resulting in a reduced number of motion vectors and hence lower bit-rate. Secondly, we propose a bi- directional motion estimation technique in the wavelet transform domain. Here, we estimate the temporal flags (direction information) only for the blocks in the lowest resolution subimages and use the same information for the corresponding blocks in the higher resolution subimages. The proposed techniques provide a superior coding performance compared to MRME technique.
Wavelet transform is becoming increasingly important in image compression applications because of its flexibility in representing nonstationary signals. In wavelet-based compression, coding performance can be improved by exploiting human visual system characteristics. In this paper, we propose an algorithm, optimal in the weighted mean square sense, to quantize the wavelet coefficients. The proposed algorithm provides a superior coding performance.