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A novel adaptive image zooming scheme via weighted least-squares estimation

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Abstract

A critical issue in image interpolation is preserving edge detail and texture information in images when zooming. In this paper, we propose a novel adaptive image zooming algorithm using weighted least-square estimation that can achieve arbitrary integer-ratio zoom (WLS-AIZ) For a given zooming ratio n, every pixel in a low-resolution (LR) image is associated with an n × n block of high-resolution (HR) pixels in the HR image. In WLS-AIZ, the LR image is interpolated using the bilinear method in advance. Model parameters of every n×n block are worked out through weighted least-square estimation. Subsequently, each pixel in the n × n block is substituted by a combination of its eight neighboring HR pixels using estimated parameters. Finally, a refinement strategy is adopted to obtain the ultimate HR pixel values. The proposed algorithm has significant adaptability to local image structure. Extensive experiments comparing WLS-AIZ with other state of the art image zooming methods demonstrate the superiority of WLS-AIZ. In terms of peak signal to noise ratio (PSNR), structural similarity index (SSIM) and feature similarity index (FSIM), WLS-AIZ produces better results than all other image integer-ratio zoom algorithms.

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Author information

Authors and Affiliations

  1. Cyber Physical System Research and Development Center, The Third Research Institute of Ministry of Public Security, Shanghai, 201204, China

    Xuexia Zhong, Jian Wang & Wenfei Wang

  2. School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China

    Guorui Feng

  3. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Jian Wang

  4. Shanghai Chenrui Information Technology Company, Shanghai, 201204, China

    Jian Wang

  5. College of Information and Computer Science, Shanghai Business School, Shanghai, 201400, China

    Wen Si

Authors
  1. Xuexia Zhong
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  2. Guorui Feng
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  3. Jian Wang
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  4. Wenfei Wang
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  5. Wen Si
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Corresponding author

Correspondence to Guorui Feng.

Additional information

Xuexia Zhong received her BS from Shandong Institute of Business and Technology, China in 2007, and her MS in communication and information systems from Shanghai University, China in 2014. Currently, she works in the Cyber Physical Systems Research and Development Center, the Third Research Institute of the Ministry of Public Security, China. Her research interests include image processing, multimedia communication, and self-organizing networks.

Guorui Feng received his BS and MS in computational mathematics from Jilin University, China in 1998 and 2001 respectively. He received his PhD in electronic engineering from Shanghai Jiaotong University, China 2005. From January to December in 2006, he was an assistant professor in East China Normal University, China. During 2007, he was a research fellow in Nanyang Technological University, Singapore. Now he is with the School of Communication and Information Engineering, Shanghai University, China. His current research interests include pattern recognition, image processing, image content security and computational intelligence.

Jian Wang received his BS and MS in mechanical engineering from Nanjing University of Aeronautics and Astronautics (NUAA), China in 2001 and 2005, respectively, and his PhD in mechanical engineering from Shanghai Jiaotong University, China. He is currently an associate researcher at the Third Research Institute of the Ministry of Public Security, China. His research interests include computer vision, pattern recognition, artificial intelligence, and equipment automation.

Wenfei Wang received his BS in control systems from Zhejiang University, China in 2005 and his PhD in control science and engineering from Zhejiang University in 2011. Since June 2011, he has been an assistant researcher at the Third Research Institute of the Ministry of Public Security, China. His research interests are image processing and recognition, and Simultaneous localization and building (SLAM).

Wen Si received his PhD from the School of Communication and Information Engineering, Shanghai University, China in 2011. He is currently an associate professor at the College of Information and Computer Science, Shanghai Business School, China. He has published over 20 papers in international journals and conferences in the areas of wearable sensors and information systems. He has registered three national invention patents in the areas of novel sensors and static marks. His main research interests include wireless sensor networks and data gathering.

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Zhong, X., Feng, G., Wang, J. et al. A novel adaptive image zooming scheme via weighted least-squares estimation. Front. Comput. Sci. 9, 703–712 (2015). https://doi.org/10.1007/s11704-015-4179-x

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  • DOI: https://doi.org/10.1007/s11704-015-4179-x

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