Super resolution combination methods for CCTV forensic interpretation

Generating a quality high resolution image has become an essential for variety purposes especially in forensic field. Compressed and at low resolution video frames of common security surveillance videos are found to be very low in clarity and degraded with many noises, distortions, blurs, bad illumination and video compression artifact. This could interfere during image interpretation and analysis process. This paper proposed a combination of super resolution methods for image processing. Using super resolution methods, high resolution image is obtained from a set of low resolution images, after it had undergone two main processes; image registration process based on Keren algorithm and image reconstruction process based on Projection onto Convex Set (POCS) on frequency domain. The validation process of output is done by calculating the Peak Signal to Noise Ratio (PSNR) value to show the comparison of image quality. The experimental results have shown that our proposed combinatorial method based super resolution and nearest neighbor methods outperformed other state-of-the-art methods.

[1]  Michael Elad,et al.  Generalizing the Nonlocal-Means to Super-Resolution Reconstruction , 2009, IEEE Transactions on Image Processing.

[2]  Shmuel Peleg,et al.  Image sequence enhancement using sub-pixel displacements , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Jianya Gong,et al.  POCS Super-Resolution Sequence Image Reconstruction Based on Improvement Approach of Keren Registration Method , 2006, Sixth International Conference on Intelligent Systems Design and Applications.

[4]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[5]  Maria Petrou,et al.  Super resolution: an overview , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[6]  John H. Reif,et al.  Super-Resolution Video Analysis for Forensic Investigations , 2007, IFIP Int. Conf. Digital Forensics.

[7]  Nelson D. A. Mascarenhas,et al.  Multispectral image data fusion using POCS and super-resolution , 2006, Comput. Vis. Image Underst..

[8]  Wan-Chi Siu,et al.  Single image super-resolution using Gaussian process regression , 2011, CVPR 2011.

[9]  Siti Norul Huda Sheikh Abdullah,et al.  Multiple-frames super-resolution for closed circuit television forensics , 2011, 2011 International Conference on Pattern Analysis and Intelligence Robotics.

[10]  Eamon B. Barrett,et al.  Super-resolution image synthesis using projections onto convex sets in the frequency domain , 2005, IS&T/SPIE Electronic Imaging.

[11]  William T. Freeman,et al.  Example-Based Super-Resolution , 2002, IEEE Computer Graphics and Applications.

[12]  Xin Fan,et al.  A learning-based POCS algorithm for face image super-resolution reconstruction , 2005, International Conference on Machine Learning and Computing.