Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems


Kara A. O. , Okman O. E. , Aytac T.

INFRARED PHYSICS & TECHNOLOGY, vol.54, no.5, pp.382-394, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 54 Issue: 5
  • Publication Date: 2011
  • Doi Number: 10.1016/j.infrared.2011.05.003
  • Journal Name: INFRARED PHYSICS & TECHNOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.382-394
  • Keywords: Image enhancement, Imaging infrared systems, Feature extraction, Clustering of wavelet coefficients, Target detection, Sea surveillance systems, ALGORITHM, EDGE
  • Middle East Technical University Affiliated: Yes

Abstract

Most of the techniques developed for infrared (IR) image enhancement (IE) depend heavily on the scene, environmental conditions, and the properties of the imaging system. So, with a set of predefined scenario properties, a content-based IR-IE technique can be developed for better situational awareness. This study proposes an adaptive IR-IE technique based on clustering of wavelet coefficients of an image for sea surveillance systems. Discrete wavelet transform (DWT) of an image is computed and feature vectors are constructed from subband images. Clustering operation is applied to group similar feature vectors that belong to different scene components such as target or background. Depending on the feature vectors, a weight is assigned to each cluster and these weights are used to compute gain matrices which are used to multiply wavelet coefficients for the enhancement of the original image. Enhancement results are presented and a comparison of the performance of the proposed algorithm is given through subjective tests with other well known frequency and histogram based enhancement techniques. The proposed algorithm outperforms previous ones in the truthfulness, detail visibility of the target, artificiality, and total quality criteria, while providing an acceptable computational load. (C) 2011 Elsevier B.V. All rights reserved.