• DocumentCode
    693123
  • Title

    An integrated bilateral and unsharp masking filter for image contrast enhancement

  • Author

    Haiyan Shi ; Ngaiming Kwok

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Shaoxing Univ., Shaoxing, China
  • Volume
    02
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    907
  • Lastpage
    912
  • Abstract
    Noise reduction and contrast enhancement are the two fundamental procedures in most image processing applications. Their effectiveness often play crucial roles in the success of subsequent image operations such as feature segmentation or object recognition. In order to obtain high quality images, the bilateral filer (BF) and the unsharp masking filter (UMF) have often been used as attractive candidates for their proven performances in noise removal and contrast enhancement. The BF is able to remove noises while preserving edge sharpness. On the other hand, the UMF is capable of increasing image contrast. Since the BF is not designed for contrast enhancement and the UMF is not developed for noise reduction, their strengths may not be fully utilized for image quality improvement. In this work, the two filters are integrated in a pipelined process such that the resultant image noise is reduced while the contrast is increased. Experimental results on public-domain and real-life test images demonstrate the effectiveness of the proposed approach.
  • Keywords
    edge detection; feature extraction; image denoising; image enhancement; image segmentation; object recognition; UMF; edge sharpness; feature segmentation; image contrast enhancement; image noise; image processing applications; image quality improvement; integrated bilateral filter; noise reduction; noise removal; object recognition; unsharp masking filter; Abstracts; Gain measurement; Kernel; Robots; Signal to noise ratio; Bilateral filter; Contrast enhancement; Noise removal; Unsharp masking filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890412
  • Filename
    6890412