Publications (59)0 Total impact
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ABSTRACT: A perceptually optimised approach to sign language video coding is presented. The proposed approach is based on the results (included) of an eye tracking study in the visual attention of sign language viewers. Results show reductions in bit rate of over 30% with very good subjective quality.
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ABSTRACT: This paper describes a spatial error concealment method that uses edge related information for concealing missing macroblocks in a way that not only preserves existing edges but also avoids introducing new strong ones. The method relies on a novel switching algorithm which uses the directional entropy of neighboring edges for choosing between two interpolation methods, a directional along detected edges or a bilinear using the nearest neighboring pixels. Results show that the performance of the proposed method is subjectively and objectively (PSNR wise) better compared to both 'single interpolation' and to edge strength based switching methods This work was performed as part of the European Union FP6 WCAM project
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ABSTRACT: A real-time, non-iterative, multi-view depth estimation algorithm is presented. Based on the postulate that regions of similar colour in an image have similar depths, a novel filter is proposed which seeks to minimize the error associated with a given depth while preserving possible depth discontinuities at colour boundaries.
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ABSTRACT: Nonlinear distributed tracking for a single target is addressed in this paper. This problem consists of tracking a target of interest while moving the sensors to `best' positions according to an critera appropriate for the problem. Both target tracking and manoeuvring of sensors are carried out jointly using a novel Sequential Monte Carlo technique. The proposed technique is illustrated using a bearing-only problem and simulations are used to compare the performance of the proposed technique with distributed tracking using fixed sensors. This work forms a part of the DIF-DTC project whose funding and support is gratefully acknowledged.
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ABSTRACT: We present a novel image fusion algorithm based on ICA that has an improved performance over sensor networks. It employs segmentation to determine the most important regions in the input images and consequently fuses the ICA coefficients from the given regions. Sparse coding of the coefficients in ICA domain is used to minimize noise transferred from input images into the fused output. Experimental results confirm that the proposed method outperforms other state-of- the-art methods in the sensor network environment, characterized by JPEG 2000 compression and data packetization
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ABSTRACT: A novel algorithm for disparity/depth estimation from multi-view images is presented. A dynamic programming approach with window-based correlation and a novel cost function is proposed. The smoothness of disparity/depth map is embedded in dynamic programming approach, whilst the window-based correlation increases reliability. The enhancement methods are included, i.e. adaptive window size and shiftable window are used to increase reliability in homogenous areas and to increase sharpness at object boundaries. First, the algorithms estimate depth maps along a single camera axis. The algorithms exploits then combines the depth estimates from different axis to derive a suitable depth map for multi-view images. The proposed scheme outperforms existing approaches in parallel and in the non-parallel camera configurations
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ABSTRACT: The colour volumetric data which is constructed from a set of multi-view images is capable of providing realistic immersive experience. However it is not widely applicable due to its manifold increase in bandwidth. This paper presents a novel framework to achieve scalable volumetric compression. Based on wavelet transformation, data rearrangement algorithm is proposed to compact volumetric data leading to high efficiency of transformation. The colour data is also rearranged by using the characteristics of human eye sensitivity. Moreover, the pre-processing for adaptive resolution is proposed in this paper. The low resolution overcomes the limitation of the data transmission at low bit rate, whilst the fine resolution improves the synthesised images' quality. The results of our proposed schemes show significant improvement of the compression performance over the traditional 3D coding.
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ABSTRACT: With accompanying conference presentation A novel technique for exploring the use of indexing metadata in improving coding efficiency is proposed in this paper. The technique uses an MPEG-7 descriptor as the basis for a fast mode decision algorithm for H.264/AVC encoders. The descriptor is used to form homogenous clusters for each frame, within which limited available coding modes for each macroblock are defined. The coding mode of an already coded macroblock that belongs to the same cluster in the same frame as well as the statistics of the coding modes of similar clusters in previous frames, are used for limiting the range of available coding modes within each cluster. The results show that the proposed algorithm is able to achieve an average of 47% time-saving when compared to the full search method and 21% when compared to the fast mode decision algorithm employed in the JM12.2 reference H.264 software encoder. In both cases, results yield only a small degradation in rate-distortion performance and a negligible loss in subjective quality
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ABSTRACT: This paper describes a modified rate control algorithm for H.264 that can accommodate multiple priority levels given a region of interest (Rol). The modified method allows better control of the quality of the Rol and gradual variation of the quality in the rest of the video frame through a bit redistribution process that is based on a number of parameters, including characteristics of the Rol, user input and perceptual factors.
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ABSTRACT: We propose the use of robust watermarks to enable the characterisation of attacks even after lossy compression, such as JPEG and JPEG2000. A previously constructed Bayesian framework is used to allow characterisation of attacks from a predetermined library, and the double watermarking technique as earlier proposed by the authors is employed to generate the features used to drive the classifier. The results show that the developed techniques perform well for both types of compression.
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ABSTRACT: In this paper we formulate an optimized temporal error concealment approach for H.264 based on the study of the performance of several temporal concealment features that apply to the different steps of the proposed method. Specifically we study how the concealment performance is affected by matching error measures, motion vector candidates and estimation enhancements. We show that the resulting formulated method performs significantly better than other state of the art methods. The proposed approach can prove very valuable to the mitigation of errors typically encountered with video transmission over wireless networks This work was performed as part of the European Union FP6 WCAM project
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ABSTRACT: In this paper we present a novel algorithm for fusion of multimodal surveillance images, based on ICA, which has an improved performance over sensor networks. Improvements have been demonstrated through separate training process for different modalities and the use of a fusion metric to maximise the quality of the fused image. Sparse coding of the coefficients in ICA domain is used to minimize noise transferred from input images into the fused output. Experimental results confirm that the proposed method outperforms other state-of-the-art methods in the sensor network environment, characterized by JPEG 2000 compression and data packetization. This work has been funded by the UK Data and Information Fusion Defence Technology Centre (DIF DTC).
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ABSTRACT: A new method for multimodal image fusion, based on statistical modelling of wavelet coefficients, is proposed in this paper. The algorithm draws from the weighted average scheme, but incorporates Laplacian bivariate parent-child statistical dependencies. The interscale dependency is brought in the form of shrinkage functions. The proposed method has been shown to perform very well with noisy datasets, outperforming other conventional methods in terms of fusion quality and noise reduction in the fused output The authors are grateful to the financial support by the UK MOD Data and Information Fusion Defence Technology Centre, for project 'Applied Multi-dimensional Fusion'.
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ABSTRACT: This paper describes a new methodology for multimodal image fusion based on non-Gaussian statistical modelling of wavelet coefficients of the input images. The use of families of generalised Gaussian and alpha-stable distributions for modelling image wavelet coefficients is investigated and methods for estimating distribution parameters are proposed. Improved techniques for image fusion are developed, by incorporating these models into the weighted average image fusion algorithm. The superior performance of the proposed methods is demonstrated using multimodal image datasets The authors are grateful for the financial support offered to project 2.1 'Image and video sensor fusion' by the UK MOD Data and Information Fusion Defence Technology Centre
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ABSTRACT: We describe an image fusion algorithm for data exhibiting heavy tails with no convergent second- or higher-order moments. Our developments rely on recent results showing that wavelet decomposition coefficients of images are best modeled by alpha-stable distributions, a family of heavy-tailed densities. Thus, in the multiscale wavelet domain we develop a novel fusion rule based on fractional lower order moments (FLOM's). Simulation results show that our method achieves better performance in comparison with previously proposed pixel-level fusion approaches.
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ABSTRACT: We present a new approach to 3-D image fusion using a 3-D separable wavelet transform. Several known 2-D WT fusion schemes have been extended to handle 3-D images and some new image fusion schemes (i.e. fusion by hard and soft thresholding, composite fusion, fusion of the WT maxima graphs) have been proposed. The goal of this paper is to present the new framework for 3-D image fusion using the wavelet transform, rather than to compare the results of the various fusion rules. Wavelet transform fusion diagrams have been introduced as a convenient tool to visually describe different image fusion schemes. A very important advantage of using 3-D WT image fusion over alternative image fusion algorithms is that it may be combined with other 3-D image processing algorithms working in the wavelet domain, such as `smooth versus textured' region segmentation, volume compression, where only a small part of all wavelet coefficients are preserved, and volume rendering, where the volume rendering integral is approximated using multiresolution spaces. The integration of 3-D WT image fusion in the broader framework of 3-D WT image processing and visualisation is the ultimate goal of the present study
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ABSTRACT: The widespread adoption of digital video techniques has generated a requirement for authenticity verification in applications such as criminal evidence, insurance claims and commercial databases. The paper investigates the performance, effectivity and efficiency of a spatial digital watermark designed for video authentication. The embedded watermark is estimated from the possible tampered frame with the use of a temporal filter and the motion information. The imperceptible digital stamp is robustly embedded prior to encoding (compression) and allows tamper characterisation of time-base attacks. The functionality of this system is evaluated within an MPEG-4 implementation
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ABSTRACT: This paper presents region of interest (ROI) coding of volumetric medical images with the region itself being three dimensional. An extension to 3D-SPIHT which allows 3D ROI coding is proposed. ROI coding enables faster reconstruction of diagnostically useful regions in volumetric datasets by assigning higher priority to them in the bitstream. It also introduces the possibility for increased compression performance, by allowing certain parts of the volume to be coded in a lossy manner while others are coded losslessly. Results presented highlight the benefits of the ROI extension. Additionally, a visualisation specific ROI coding case is examined. Results show the advantages of ROI coding in terms of the quality of the visualised decoded volume.
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ABSTRACT: Three-dimensional wavelet coding of volumetric medical images provides better coding performance compared to corresponding 2D methods by exploiting the inter-slice correlation that exists in such data. It introduces however latencies when it comes to transmitting specific parts of the volume. This paper presents an extension to 3D-SPlHT which allows 3D region of interest (ROI) coding. ROI coding enables faster reconstruction of diagnostically useful regions in volumetric datasets by assigning higher priority to them in the bitstream. It also introduces the possibility for increased compression performance, by allowing certain parts of the volume to be coded in a lossy manner while others are coded losslessly. The necessary modifications to 3D-SPIHT for ROI coding are described and methods for specifying a 3D ROI without adding a significant overhead are suggested. Results are presented highlighting the benefits of the ROI extension.
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ABSTRACT: The widespread adoption of digital video techniques has generated a requirement for authenticity verification in applications such as criminal evidence, insurance claims and commercial databases. This work addresses problems that arise from a spatial digital watermarking technique developed to detect frame reordering and dropping scenarios. It discusses the differences between mutual frame types at different bit-rates. Many papers consider detection after MPEG-2 decoding as a naive approach. However, this approach does offer significant advantages for a slight increase of computation load. This paper also establishes a link between the detector performance and the sequence content. The uniqueness of this work is the comparison of the test results using 18 different standard MPEG test-sequences. The functionality of the algorithm is demonstrated with a simulated attack. This work was supported by Motorola Laboratory UK and EPSRC under grant number GR/M81885
