Multi-object digital auto-focusing using image fusion

  • Authors:

  • Jeongho Shin;Vivek Maik;Jungsoo Lee;Joonki Paik

  • Affiliations:

  • Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Lab., Department of Image Engineering, Graduate School of Advanced Imaging, Multimedia, and Film, Chung-Ang University, Seoul, Korea

  • Venue:
  • ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
  • Year:
  • 2005

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Abstract

This paper proposes a novel digital auto-focusing algorithm using image fusion, which restores an out-of-focus image with multiple, differently out-of-focus objects. The proposed auto-focusing algorithm consists of (i) building a prior set of point spread functions (PSFs), (ii) image restoration, and (iii) fusion of the restored images. Instead of designing an image restoration filter for multi-object auto-focusing, we propose an image fusion-based auto-focusing algorithm by fusing multiple, restored images based on prior estimated set of PSFs. The prior estimated PSFs overcome heavy computational overhead and make the algorithm suitable for real-time applications. By utilizing both redundant and complementary information provided by different images, the proposed fusion algorithm can restore images with multiple, out-of-focus objects. Experimental results show the performance of the proposed auto-focusing algorithm.