Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Publication
- File Type
Articles 1 - 30 of 39
Full-Text Articles in Physical Sciences and Mathematics
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Dr Lei Yi
Colour and texture visual descriptors have been developed to represent structural features of images, mainly under the Query-by- Example (QBE) image retrieval paradigm. This paper explores applicability of MPEG-7 visual descriptors to describe and measure evolutional changes in image time sequences, using a fruit rotting process as an example. The research found that MPEG-7 visual descriptors can be applied to describe evolutional changes in image time sequences. The experimental results are provided using bananas captured in image time sequences. The results show the desirable monotonicity of description metrics of MPEG-7 similarity matching for image time sequences and their sensitivity to …
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Dr Lei Yi
The use of low-level feature descriptors is pervasive in content-based image retrieval tasks and the answer to the question of how well these features describe users’ intention is inconclusive. In this paper we devise experiments to gauge the degree of alignment between the description of target images by humans and that implicitly provided by low-level image feature descriptors. Data was collected on how humans perceive similarity in images. Using images judged by humans to be similar, as ground truth, the performance of some MPEG-7 visual feature descriptors were evaluated. It is found that various descriptors play different roles in different …
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Dr Fok Hing Chi Tivive
In this paper, we propose a new technique for image fusion in multi-view through-the-wall radar imaging system. As most existing image fusion methods for through-the-wall radar imaging only consider a global fusion operator, it is desirable to consider the differences between each pixel using a local operator. Here, we present a fuzzy logic-based method for pixel-wise image fusion. The performance of the proposed method is evaluated on both simulated and real data from through-the-wall radar imaging system. Experimental results show that the proposed method yields improved performance, compared to existing methods.
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Associate Professor Wanqing Li
The use of low-level feature descriptors is pervasive in content-based image retrieval tasks and the answer to the question of how well these features describe users’ intention is inconclusive. In this paper we devise experiments to gauge the degree of alignment between the description of target images by humans and that implicitly provided by low-level image feature descriptors. Data was collected on how humans perceive similarity in images. Using images judged by humans to be similar, as ground truth, the performance of some MPEG-7 visual feature descriptors were evaluated. It is found that various descriptors play different roles in different …
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Associate Professor Wanqing Li
This paper presents a way to model the cross-talk effect in CMOS image sensors. Two algorithms are derived from the model; both of them work on the Bayer raw data and have low computational complexity. Experiments on Macbeth color chart and real images have shown the effectiveness of the modeling to eliminate the cross-talk effect and produce better quality images with traditional color interpolation and correction algorithms designed for CCD image sensors.
Optimal Image Watermark Decoding, Wenming Lu, Wanqing Li, Reihaneh Safavi-Naini, Philip Ogunbona
Optimal Image Watermark Decoding, Wenming Lu, Wanqing Li, Reihaneh Safavi-Naini, Philip Ogunbona
Associate Professor Wanqing Li
Not much has been done in utilizing the available information at the decoder to optimize the decoding performance of watermarking systems. This paper focuses on analyzing different decoding methods, namely, Minimum Distance, Maximum Likelihood and Maximum a-posteriori decoding given varying information at the decoder in the blind detection context. Specifically, we propose to employ Markov random fields to model the prior information given the embedded message is a structured logo. The application of these decoding methods in Quantization Index Modulation systems shows that the decoding performance can be improved by Maximum Likelihood decoding that exploits the property of the attack …
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
Associate Professor Wanqing Li
In the state-of-the-art video-based smoke detection methods, the representation of smoke mainly depends on the visual information in the current image frame. In the case of light smoke, the original background can be still seen and may deteriorate the characterization of smoke. The core idea of this paper is to demonstrate the superiority of using smoke component for smoke detection. In order to obtain smoke component, a blended image model is constructed, which basically is a linear combination of background and smoke components. Smoke opacity which represents a weighting of the smoke component is also defined. Based on this model, …
Image Reconstruction From Sparse Projections Using S-Transform, Jianhua Luo, Jiahai Liu, Wanqing Li, Yuemin Zhu, Ruiyao Jiang
Image Reconstruction From Sparse Projections Using S-Transform, Jianhua Luo, Jiahai Liu, Wanqing Li, Yuemin Zhu, Ruiyao Jiang
Associate Professor Wanqing Li
Sparse projections are an effective way to reduce the exposure to radiation during X-ray CT imaging. However, reconstruction of images from sparse projection data is challenging. This paper introduces a new sparse transform, referred to as S-transform, and proposes an accurate image reconstruction method based on the transform. The S-transform effectively converts the ill-posed reconstruction problem into a well-defined one by representing the image using a small set of transform coefficients. An algorithm is proposed that efficiently estimates the S-transform coefficients from the sparse projections, thus allowing the image to be accurately reconstructed using the inverse S-transform. The experimental results …
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li
Associate Professor Wanqing Li
Colour and texture visual descriptors have been developed to represent structural features of images, mainly under the Query-by- Example (QBE) image retrieval paradigm. This paper explores applicability of MPEG-7 visual descriptors to describe and measure evolutional changes in image time sequences, using a fruit rotting process as an example. The research found that MPEG-7 visual descriptors can be applied to describe evolutional changes in image time sequences. The experimental results are provided using bananas captured in image time sequences. The results show the desirable monotonicity of description metrics of MPEG-7 similarity matching for image time sequences and their sensitivity to …
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Dr Igor Kharitonenko
This paper presents a way to model the cross-talk effect in CMOS image sensors. Two algorithms are derived from the model; both of them work on the Bayer raw data and have low computational complexity. Experiments on Macbeth color chart and real images have shown the effectiveness of the modeling to eliminate the cross-talk effect and produce better quality images with traditional color interpolation and correction algorithms designed for CCD image sensors.
Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim
Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim
Dr Ahmed Mohamed Ahmed Haidar
Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical systems are expensive in terms of plant downtime, damage, loss of production or risk from fire. If the threshold temperature is timely detected, the electrical equipment failures can be avoided. This paper presents a straightforward approach for thermal analysis that examines power loads and large area thermal characteristics. A thermal imaging camera was used to collect thermal pictures of the tested system under …
Fast Quality-Guided Phase Unwrapping Algorithm For 3d Profilometry Based On Object Image Edge Detection, Ke Chen, Jiangtao Xi, Yanguang Yu
Fast Quality-Guided Phase Unwrapping Algorithm For 3d Profilometry Based On Object Image Edge Detection, Ke Chen, Jiangtao Xi, Yanguang Yu
Dr Yanguang Yu
A main challenge associated with 3-dimentional fringe pattern profilometry (3D-FPP) systems is the unwrapping of phase maps resulted from complex object surface shapes with both robustness and speed guaranteed. In this paper we propose a new quality-guided phase unwrapping algorithm. In contrast to the conventional quality-guided methods, we classify pixels on wrapped phase map into two types by detecting edge pixels on object image: high quality (HQ) pixels corresponding to smooth phase changes and low quality (LQ) ones to rough phase changes. In order to improve the computational efficiency, these two types of pixels are unwrapped by means of different …
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
A Novel Video-Based Smoke Detection Method Using Image Separation, Hongda Tian, Wanqing Li, Lei Wang, Philip Ogunbona
Dr Lei Wang
In the state-of-the-art video-based smoke detection methods, the representation of smoke mainly depends on the visual information in the current image frame. In the case of light smoke, the original background can be still seen and may deteriorate the characterization of smoke. The core idea of this paper is to demonstrate the superiority of using smoke component for smoke detection. In order to obtain smoke component, a blended image model is constructed, which basically is a linear combination of background and smoke components. Smoke opacity which represents a weighting of the smoke component is also defined. Based on this model, …
A Novel Multi-Image Query Techniques For Automatic Query Concept Capture, Fenghui Ren, Philip Ogunbona, Lei Ye
A Novel Multi-Image Query Techniques For Automatic Query Concept Capture, Fenghui Ren, Philip Ogunbona, Lei Ye
Dr Fenghui Ren
No abstract provided.
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Associate Professor Golshah Naghdy
A new shape adaptive predictive lossless image coder is proposed. Three classes of block shapes are delineated with associated “optimum” predctors. Each image is partitioned into sub-blocks that are classified into one of the three classes using vector quantisation. The encoder then employs the predictor corresponding to the class of the block under consideration. Performance evaluation of the proposed coder in comparison with four other lossless coders includmg lossless JPEG indicates its superiority.
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Fuzzy Logic-Based Image Fusion For Multi-View Through-The-Wall Radar, Cher Hau Seng, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Moeness G. Amin
Professor Salim Bouzerdoum
In this paper, we propose a new technique for image fusion in multi-view through-the-wall radar imaging system. As most existing image fusion methods for through-the-wall radar imaging only consider a global fusion operator, it is desirable to consider the differences between each pixel using a local operator. Here, we present a fuzzy logic-based method for pixel-wise image fusion. The performance of the proposed method is evaluated on both simulated and real data from through-the-wall radar imaging system. Experimental results show that the proposed method yields improved performance, compared to existing methods.
Automatic Parameter Selection For Feature-Enhanced Radar Image Restoration, Moeness G Amin, Cher Hau Seng, Son Lam Phung, Abdesselam Bouzerdoum
Automatic Parameter Selection For Feature-Enhanced Radar Image Restoration, Moeness G Amin, Cher Hau Seng, Son Lam Phung, Abdesselam Bouzerdoum
Professor Salim Bouzerdoum
In this paper, we propose a new technique for optimum parameter selection in non-quadratic radar image restoration. Although both the regularization hyper-parameter and the norm value are influential factors in the characteristics of the formed restoration, most existing optimization methods either require memory intensive computation or prior knowledge of the noise. Here, we present a contrast measure-based method for automated hyper-parameter selection. The proposed method is then extended to optimize the norm value used in non-quadratic image formation and restoration. The proposed method is evaluated on the MSTAR public target database and compared to the GCV method. Experimental results show …
A Gaussian-Rayleigh Mixture Modeling Approach For Through-The-Wall Radar Image Segmentation, Cher Hau Seng, Abdesselam Bouzerdoum, Moeness Amin, F Ahmad
A Gaussian-Rayleigh Mixture Modeling Approach For Through-The-Wall Radar Image Segmentation, Cher Hau Seng, Abdesselam Bouzerdoum, Moeness Amin, F Ahmad
Professor Salim Bouzerdoum
In this paper, we propose a Gausssian-Rayleigh mixture modeling approach to segment indoor radar images in urban sensing applications. The performance of the proposed method is evaluated on real 2D polarimetric data. Experimental results show that the proposed method enhances image quality by distinguishing between target and clutter regions. The proposed method is also compared to an existing Neyman-Pearson (NP) target detector that has been recently devised for through-the-wall radar imaging. Performance evaluation of both methods shows that the proposed method outperforms the NP detector in enhancing the input images.
Adaptive Regularization For Multiple Image Restoration Using An Extended Total Variations Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Adaptive Regularization For Multiple Image Restoration Using An Extended Total Variations Approach, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Professor Salim Bouzerdoum
In this paper a Variational Inequality method for multiple in- put, multiple output image restoration is presented using an extended Total Variations (TV) regularizer. This approach calculates an adaptive regularization parameter for each image based on their respective degradations. The proposed ex- tended Total Variations regularizer combines both intra-image and inter-image pixel information for improved restoration performance. Hyperparameters for controlling this new TV measure are calculated using a Bayesian joint maximum a posteriori approach.
A Compressive Sensing Approach To Image Restoration, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
A Compressive Sensing Approach To Image Restoration, Matthew Kitchener, Abdesselam Bouzerdoum, Son Lam Phung
Professor Salim Bouzerdoum
In this paper the image restoration problem is solved using a Compressive Sensing approach, and the translation invariant, a Trous, undecimated wavelet transform. The problem is cast as an unconstrained optimization problem which is solved using the Fletcher-Reeves nonlinear conjugate gradient method. A comparison based on experimental results shows that the proposed method achieves comparable if not better performance as other state-of-the-art techniques.
A New Approach To Sparse Image Representation Using Mmv And K-Svd, Jie Yang, Abdesselam Bouzerdoum, Son Lam Phung
A New Approach To Sparse Image Representation Using Mmv And K-Svd, Jie Yang, Abdesselam Bouzerdoum, Son Lam Phung
Professor Salim Bouzerdoum
This paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogonal matching pursuit MMV (OMPMMV) methods, the proposed method runs faster and achieves a higher overall reconstruction accuracy.
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Perceived Similarity And Visual Descriptions In Content-Based Image Retrieval, Yuan Zhong, Lei Ye, Wanqing Li, Philip Ogunbona
Professor Philip Ogunbona
The use of low-level feature descriptors is pervasive in content-based image retrieval tasks and the answer to the question of how well these features describe users’ intention is inconclusive. In this paper we devise experiments to gauge the degree of alignment between the description of target images by humans and that implicitly provided by low-level image feature descriptors. Data was collected on how humans perceive similarity in images. Using images judged by humans to be similar, as ground truth, the performance of some MPEG-7 visual feature descriptors were evaluated. It is found that various descriptors play different roles in different …
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Modelling Of Color Cross-Talk In Cmos Image Sensors, Wanqing Li, Philip Ogunbona, Yan Shi, Igor Kharitonenko
Professor Philip Ogunbona
This paper presents a way to model the cross-talk effect in CMOS image sensors. Two algorithms are derived from the model; both of them work on the Bayer raw data and have low computational complexity. Experiments on Macbeth color chart and real images have shown the effectiveness of the modeling to eliminate the cross-talk effect and produce better quality images with traditional color interpolation and correction algorithms designed for CCD image sensors.
Application Of Visual Modelling In Image Restoration And Colour Image Processing, Aziz Qureshi, Philip Ogunbona
Application Of Visual Modelling In Image Restoration And Colour Image Processing, Aziz Qureshi, Philip Ogunbona
Professor Philip Ogunbona
This paper describes the application of human visual models in (i) defining a visually uniform colour representation space and (ii) the formulation of visually weighted Kalman filtering for image restoration. The former being useful in colour image quantisation and compression. For (i), the uniformity of chromaticity differences at the ouptut of Frei ’s colour vision model [3] is tested and compensated for by using MacAdam’s uniform chromaticity space. For (ii), the dynamical image model of the Kalman filter is visually weighted using the frequency response of Stockham’s model [l] of human vision.
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Factorised Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
No abstract provided.
Image Compression Based On Genealogical Relation Of The Tsvq Indices, Jamshid Shanbehzadeh, Philip Ogunbona, Abdoihosein Sarafzadeh
Image Compression Based On Genealogical Relation Of The Tsvq Indices, Jamshid Shanbehzadeh, Philip Ogunbona, Abdoihosein Sarafzadeh
Professor Philip Ogunbona
The indices obtained by tree-structured vector quantisation (TSVQ) have an interesting property that enables them to give information about the correlation between two image blocks. Iftwo image blocks are highly correlated, they may have an identical index, or the same ancestors. The existence of high inter-block correlation in natural images results in having neighboring blocks with the same genealogy. This characteristic can be used to compress the indices. This paper introduces a novel method to exploit the genealogical relation between the image block indices obtained from a TSVQ. The performance of this scheme in terms of PSNR versus average rate …
Edge Image Description Using Fractal Interpolation, P Motallebi, P O. Ogunbona
Edge Image Description Using Fractal Interpolation, P Motallebi, P O. Ogunbona
Professor Philip Ogunbona
Edge images derived from compressed image databases are described using fractal techniques. The proposed method is able to give affine transformation-invariant description suitable for use in a query-by-example database application. Comparison among the proposed method, polynomial interpolation and spline interpolation is given. It is concluded that fractal interpolation can give a compact description of image contours and is able to cope with random perturbation of the coordinates of the contour points by as much as 25 percent.
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Coding Gain And Spatial Localisation Properties Of Discrete Wavelet Transform Filters For Image Coding, J Andrew, P Ogunbona, F Paoloni
Professor Philip Ogunbona
The authors consider coding gain and spatial localisation properties of DWT filters for still image compression. Using a JPEG type quantisation and encoding method several images are compressed using a DWT implemented using various two-band subband filter sets. It is concluded that a relatively high coding gain (relative to a highly correlated source) is necessary, but not sufficient, for good image coding performance. Further, it is observed that low spatial width filters are desirable, particularly in regard to reduced ringing distortion. In terms of the tradeoff between coding gain and spatial localisation, and in terms of actual coding performance, it …
Similarity Measures For Compressed Image Databases, P Sangassapaviriya, Philip Ogunbona
Similarity Measures For Compressed Image Databases, P Sangassapaviriya, Philip Ogunbona
Professor Philip Ogunbona
For image database applications it is desirable that functions such as searching, browsing and partial recall be done without the need to totally decompress the image. This has the advantage of alleviating possible burden and degradation that the network may suffer. Edge images derived from wavelet-compressed images are considered as index that can be queried by example. Zernike moment invariants are used as descriptors for the index edge image and the query sketch image. The descriptions are compared for the purpose of database searching. The query images were allowed to undergo translation, rotation, scaling and some deformation. Simulation results gave …
Content-Based Retrieval From Compressed-Image Databases, Philip Ogunbona, P Sangassapaviriya
Content-Based Retrieval From Compressed-Image Databases, Philip Ogunbona, P Sangassapaviriya
Professor Philip Ogunbona
There is an enormous amount of multi-media data including images, video, speech, audio and text, distributed among the various computer nodes on the Internet. The extent to which a user wiU be able to derive useful information from these data depends largely on the ease with which required data can be retrieved from the databases. The share volume of the data also poses a storage constraint on the databases; hence these data will need to exist in the compressed form on the databases. In this paper we concentrate on image data and propose a new paradigm in which a compressed …