Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 19 of 19
Full-Text Articles in Physical Sciences and Mathematics
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
Cher Hau Seng
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.
Image Similarity Index Based On Moment Invariants Of Approximation Level Of Discrete Wavelet Transform, Prashan Premaratne, Malin Premaratne
Image Similarity Index Based On Moment Invariants Of Approximation Level Of Discrete Wavelet Transform, Prashan Premaratne, Malin Premaratne
Dr Prashan Premaratne
Subjective quality measures based on the human visual system for images do not agree well with well-known metrics such as mean squared error and peak signal-to-noise ratio. Recently, the structural similarity measure (SSIM) has received acclaim owing to its ability to produce results on a par with the human visual system. However, experimental results indicate that noise and blur seriously degrade the performance of the SSIM metric. Furthermore, despite the SSIM's popularity, it does not provide adequate insight into how it handles the 'structural similarity' of images. Proposed is a new structural similarity measure based on the approximation level of …
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 …
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 …
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.
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.
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.
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 …
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Index Compressed Image Adaptive Vector Quantisation, Jamshid Shanbehzadeh, Philip Ogunbona
Professor Philip Ogunbona
This paper introduces an improved image adaptive vector quantisation technique - index compressed image adaptive vector quantisation (IC-IAVQ). Despite its advantage over the universal codebook VQ, basic image adaptive VQ (IAVQ) is still suboptimum; it neglects the correlation among block indices in the encoded image. The new technique, IC-IAVQ, overcomes this suboptimality through a pre-processing and lossless compression of block indices. Simulation results using several images show that IC-IAVQ outperforms IAVQ and entropy coded IAVQ, especially at low bit-rates by about 2dB on average.
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
Professor Philip Ogunbona
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 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
Professor Philip Ogunbona
No abstract provided.
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
Professor Philip Ogunbona
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 …