Adaptive guided image filtering for sharpness enhancement and noise reduction

  • Authors:
  • Cuong Cao Pham;Synh Viet Uyen Ha;Jae Wook Jeon

  • Affiliations:
  • School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea

  • Venue:
  • PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
  • Year:
  • 2011

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Abstract

Sharpness enhancement and noise reduction play crucial roles in computer vision and image processing. The problem is to enhance the appearance and reduce the noise of the digital images without causing halo artifacts. In this paper, we propose an adaptive guided image filtering (AGF) able to perform halo-free edge slope enhancement and noise reduction simulaneously. The proposed method is developed based on guided image filtering (GIF) and the shift-variant technique, part of adaptive bilateral filtering (ABF). Experiments showed the results produced from our method are superior to those produced from unsharp masking-based techniques and comparable to ABF filtered output. Our proposed AGF outperforms ABF in terms of computational complexity. It is implemented using a fast and exact linear-time algorithm.