Nishan Canagarajah

University of Bristol

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A robust automatic clustering scheme for image segmentation using wavelets

IEEE Transactions on Image Processing (1996)

Robert P. Porter Nishan Canagarajah

The optimal features with which to discriminate between regions and, thus, segment an image often differ depending on the nature of the image. Many real images are made up of both smooth and textured regions and are best segmented using different features in different areas. A scheme that automatically selects the optimal features for each pixel using wavelet analysis is proposed, leading to a robust segmentation algorithm. An automatic method for determining the optimal number of regions for segmentation is also developed.

Segmentation-based object categorization

Range segmentation

10.1109/83.491343

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Citations (117)

A data association algorithm for multiple object tracking in video sequences

Mohamed Hisham Jaward Lyudmila Mihaylova Nishan Canagarajah David Bull

This paper presents a particle filtering algorithm for multiple object tracking. The proposed particle filter (PF) embeds a data association technique based on the joint probabilistic data association (JPDA) which handles the uncertainty of the measurement origin.

Data association

Association (psychology)

Tracking (education)

10.1049/ic:20060565

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Citations (18)

A Novel Metric for Performance Evaluation of Image Fusion Algorithms

World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering (2007)

Nedeljko Cvejic Artur Łoza David Bull Nishan Canagarajah

Source

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Citations (16)

Multi-resolution parametric region tracking for 2D object replacement in video

Paul Brasnett David Bull Nishan Canagarajah

This paper develops an efficient parametric multiresolution region tracking algorithm which is applied to the task of object replacement in video sequences. The tracker relies on gradient-based techniques to provide efficient estimation of the target location and pose in each frame. The tracking algorithm improves upon similar efficient parametric algorithms by increasing the distance an object can move from frame to frame. Experimental results provide clear evidence of the improved performance over existing region tracking. The parameters that estimate the pose and location of the target are used to initialise the object replacement algorithm. The object replacement uses the pose estimates with texture mapping techniques to perform image warping of an arbitrary sized replacement image. The location estimates are used to accurately insert the replacement image into the current frame.

Tracking (education)

Image warping

10.1109/icip.2004.1419473

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Citations (0)

Video Object Mining with Local Region Tracking

Springer eBooks (2007)

Arasanathan Anjulan Nishan Canagarajah

Feature (linguistics)

Tracking (education)

10.1007/978-3-540-73417-8_24

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Citations (0)

Backward Adaptive Pixel-based Fast Predictive Motion Estimation

IEEE Signal Processing Letters (2009)

Xiaolin Chen Nishan Canagarajah Jose Nunez‐Yanez

This letter presents a novel backward adaptive pixel-based fast predictive motion estimation (BAPME) scheme for lossless video compression. Unlike the widely used block-matching motion estimation techniques, this method predicts the motion on a pixel-by-pixel basis by comparing a group of past observed pixels in two adjacent frames, eliminating the need of transmitting side information. Combined with prediction and a fast search technique, the proposed algorithm achieves better entropy results and significant reduction in computation than pixel-based full search for a set of standard test sequences. Experimental results also suggest that BAPME is superior to block-based full search in terms of speed and zero-order entropy.

Quarter-pixel motion

10.1109/lsp.2009.2016475

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Citations (8)

Statistical Model-based fusion of noisy multi-band images in the wavelet domain

Artur Łoza Alin Achim David Bull Nishan Canagarajah

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.

10.1109/icif.2007.4407977

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Citations (3)

Mobility tracking in cellular networks with sequential Monte Carlo filters

Lyudmila Mihaylova David Bull Donka Angelova Nishan Canagarajah

This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.

Tracking (education)

10.1109/icif.2005.1591843

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Citations (5)

Optimized Temporal Error Concealment through Performance Evaluation of Multiple Concealment Features

Dimitris K. Agrafiotis David Bull Nishan Canagarajah

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.

Error concealment

Motion vector

10.1109/icce.2006.1598385

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Citations (7)

Region of interest coding of volumetric medical images

D. Agraftotis David Bull Nishan Canagarajah

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. ROl 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 ROl extension.

Lossy compression

Region of interest

Bitstream

JPEG 2000

10.1109/icip.2003.1247220

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Citations (7)