Mr Shadan Khattak

Job: PhD Candidate

Faculty: Technology

School/department: School of Engineering and Sustainable Development

Research group(s): Centre for Electronic and Communications Engineering

Address: De Montfort University, The Gateway, Leicester, LE1 9BH UK

T: +44 (0) 0116 2551551

E: shadan.khattak@myemail.dmu.ac.uk

W: http://www.dmu.ac.uk

 

Research group affiliations

Centre for Electronic and Communications Engineering

Publications and outputs 

  • Temporal and Inter-view Consistent Error Concealment Technique for Multiview plus Depth Video
    Temporal and Inter-view Consistent Error Concealment Technique for Multiview plus Depth Video Khattak, Shadan; Maugey, Thomas; Hamzaoui, Raouf; Ahmad, Shakeel; Frossard, Pascal Multiview plus depth (MVD) is an emerging video format with many applications, including 3D television and free viewpoint television. During broadcast of compressed MVD video, transmission errors may cause the loss of whole frames, resulting in significant degradation of video quality. Error concealment techniques have been widely used to deal with transmission errors in video communication. However, the existing solutions do not address the requirement that the reconstructed frames be consistent with neighbouring frames, i.e., corresponding pixels have consistent color information. We propose a new consistency model for error concealment of MVD video that allows to maintain a high level of consistency between frames of the same view (temporal consistency) and those of neighbouring views (inter-view consistency). We then propose an algorithm that uses our model to implement concealment in a consistent way. Simulations with the reference software for the Multiview Video Coding project of the Joint Video Team (JVT) of the ISO/IEC MPEG and ITU-T VCEG show that our method outperforms benchmark techniques, including a baseline approach based on the Boundary Matching Algorithm, with respect to both reconstruction quality and view consistency.
  • Low Complexity Multiview Video Coding
    Low Complexity Multiview Video Coding Khattak, Shadan 3D video is a technology that has seen a tremendous attention in the recent years. Multiview Video Coding (MVC) is an extension of the popular H.264 video coding standard and is commonly used to compress 3D videos. It offers an improvement of 20% to 50% in compression efficiency over simulcast encoding of multiview videos using the conventional H.264 video coding standard. However, there are two important problems associated with it: (i) its superior compression performance comes at the cost of significantly higher computational complexity which hampers the real-world realization of MVC encoder in applications such as 3D live broadcasting and interactive Free Viewpoint Television (FTV), and (ii) compressed 3D videos can suffer from packet loss during transmission, which can degrade the viewing quality of the 3D video at the decoder. This thesis aims to solve these problems by presenting techniques to reduce the computational complexity of the MVC encoder and by proposing a consistent error concealment technique for frame losses in 3D video transmission. The thesis first analyses the complexity of the MVC encoder. It then proposes two novel techniques to reduce the complexity of motion and disparity estimation. The first method achieves complexity reduction in the disparity estimation process by exploiting the relationship between temporal levels, type of macroblocks and search ranges while the second method achieves it by exploiting the geometrical relation- ship between motion and disparity vectors in stereo frames. These two methods are then combined with other state-of-the-art methods in a unique framework where gains add up. Experimental results show that the proposed low-complexity framework can reduce the encoding time of the standard MVC encoder by over 93% while maintaining similar compression efficiency performance. The addition of new View Synthesis Prediction (VSP) modes to the MVC encoding framework improves the compression efficiency of MVC. However, testing additional modes comes at the cost of increased encoding complexity. In order to reduce the encoding complexity, the thesis, next, proposes a bayesian early mode decision technique for a VSP enhanced MVC coder. It exploits the statistical similarities between the RD costs of the VSP SKIP mode in neighbouring views to terminate the mode decision process early. Results indicate that the proposed technique can reduce the encoding time of the enhanced MVC coder by over 33% at similar compression efficiency levels. Finally, compressed 3D videos are usually required to be broadcast to a large number of users where transmission errors can lead to frame losses which can degrade the video quality at the decoder. A simple reconstruction of the lost frames can lead to inconsistent reconstruction of the 3D scene which may negatively affect the viewing experience of a user. In order to solve this problem, the thesis proposes, at the end, a consistency model for recovering frames lost during transmission. The proposed consistency model is used to evaluate inter-view and temporal consistencies while selecting candidate blocks for concealment. Experimental results show that the proposed technique is able to recover the lost frames with high consistency and better quality than two standard error concealment methods and a baseline technique based on the boundary matching algorithm.
  • Bayesian Early Mode Decision Technique for View Synthesis Prediction-Enhanced Multiview Video Coding
    Bayesian Early Mode Decision Technique for View Synthesis Prediction-Enhanced Multiview Video Coding Khattak, Shadan; Hamzaoui, Raouf; Maugey, Thomas; Ahmad, Shakeel; Frossard, Pascal View synthesis prediction (VSP) is a codingmode that predicts video blocks from synthesised frames. It is particularly useful in a multi-camera setup with large inter-camera distances. Adding a VSP-based SKIP mode to a standard Multiview Video Coding (MVC) framework improves the rate-distortion (RD) performance but increases the time complexity of the encoder. This letter proposes an earlymode decision technique for VSP SKIP-enhanced MVC. Our method uses the correlation between the RD costs of the VSP SKIP mode in neighbouring views and Bayesian decision theory to reduce the number of candidate coding modes for a given macroblock. Simulation results showed that our technique can save up to 36.20% of the encoding time without any significant loss in RD performance.
  • Fast encoding techniques for Multiview Video Coding
    Fast encoding techniques for Multiview Video Coding Khattak, Shadan; Hamzaoui, Raouf; Ahmad, Shakeel; Frossard, Pascal
  • Low-Complexity Multiview Video Coding
    Low-Complexity Multiview Video Coding Khattak, Shadan; Hamzaoui, Raouf; Ahmad, Shakeel; Frossard, Pascal We consider the problem of complexity reduction in Multiview Video Coding (MVC). We provide a unique comprehensive study that integrates and compares the different low complexity encoding techniques that have been proposed at different levels of the MVC system. In addition, we propose a novel complexity reduction method that takes advantage of the relationship between disparity vectors along time. The relationship is exploited with respect to the motion activity in the frame, as well as with the position of the frame in the Group of Pictures. We integrate this technique into our unique comprehensive framework and evaluate the performance of the resulting system in different setups. We show that the effective combination of complexity reduction techniques results in saving up to 93% in encoding time at the cost of only 0.08 dB in peak signal-to-noise ratio (PSNR) and 1.64% increase in bitrate compared to the standard MVC implementation (JMVM 6.0).

Click here to view a full listing of Shadan Khattak's publications and outputs.

Research interests/expertise

2D/3D video compression standards: H.264/AVC, MVC, HEVC, 3DVC

Low-complexity algorithms for multiview video compression

Low-complexity algorithms for depth image compression

View-synthesis and depth image based rendering techniques

Qualifications

2003 – 2007    BSc Computer Systems Engineering, NWFP University of Engineering and Technology, Pakistan

2008 – 2009    MSc Data Communication, University of Sheffield, UK

Honours and awards

2012  Laxton Bequest and Consolidated Fund Travel Award

2010-2013    PhD Studentship, De Montfort University, UK    

2008-2009  Scholarship for MSc studies, CIIT, Pakistan           

Membership of professional associations and societies

Pakistan Engineering Council

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