Publications (3)0 Total impact
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ABSTRACT: High-frequency energy distributions are important characteristics of blurry images. In this paper, directional high-pass filters are proposed to analyze blurry images. Firstly, we show that the proposed directional high-pass filters can effectively estimate the motion direction of motion blurred images. A closed-form solution for motion direction estimation is derived. It achieves a higher estimation accuracy and is also faster than previous methods. Secondly, the paper suggests two important applications of the directional high-frequency energy analysis. It can be employed to identify out-of-focus blur and motion blur, and to detect motion blurred regions in observed images. Experiments on both synthetic and real blurred images are conducted. Encouraging results demonstrate the efficacy of the proposed methods.Signal Processing: Image Communication. 08/2012; 27(7):760–771.
Conference Proceeding: An effective document image deblurring algorithm.[show abstract] [hide abstract]
ABSTRACT: Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method.The 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011, Colorado Springs, CO, USA, 20-25 June 2011; 01/2011
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ABSTRACT: The recently proposed use of the structural similarity measure, in the particle filter-based video tracker has been shown to improve the tracking performance, compared to similar methods using the colour or edge histograms and Bhattacharyya distance. However, the combined use of the structural similarity and a particle filter results in a computationally complex tracker that may not be suitable for some real time applications. In this paper, a novel fast approach to the use of the structural similarity in video tracking is proposed. The tracking algorithm presented in this work determines the state of the target (location, size) based on the gradient ascent procedure applied to the structural similarity surface of the video frame, thus avoiding computationally expensive sampling of the state space. The new method, while being computationally less expensive, performs better, than the standard mean shift and the structural similarity particle filter trackers, as shown in exemplary surveillance video sequences.
University of Technology Sydney
Sydney, New South Wales, Australia
- Centre for Innovation in IT Services Applications (iNEXT)