The effect of Laplacian filter in adaptive unsharp masking for infrared image enhancement

İlk H. G., Jane O., İlk Dağ Ö.

INFRARED PHYSICS & TECHNOLOGY, vol.54, no.5, pp.427-438, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 54 Issue: 5
  • Publication Date: 2011
  • Doi Number: 10.1016/j.infrared.2011.06.002
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.427-438
  • Keywords: Infrared image processing, Optimum Wiener filter, Descent algorithms, Peak signal-to-noise ratio, Quasi-Newton methods, Adaptive filter
  • Middle East Technical University Affiliated: Yes


Image processing, in particular image enhancement techniques have been the focal point of considerable research activity in the last decade. With the aid of an existing image enhancement technique, adaptive unsharp masking (AUM), we propose a novel kernel to be used in AUM filtering in order to enhance discontinuities which occur on the edges of targets of interest in infrared (IR) images. The proposed method uses an adaptive filter approach where an objective function is minimized by using descent algorithms. The output IR image has better sharpness and contrast adjustment for the detection of targets in terms of objective quality metrics. Hence, the proposed method ensures that the edges of the targets in IR images are sharper and that the quality of contrast adjustment has its optimum level in terms of peak signal-to-noise ratios. (C) 2011 Elsevier B.V. All rights reserved.