Signal, Image and Video Processing

, Volume 12, Issue 5, pp 905–913 | Cite as

CT scan contrast enhancement using singular value decomposition and adaptive gamma correction

  • Fathi Kallel
  • Mouna Sahnoun
  • Ahmed Ben Hamida
  • Khalil Chtourou
Original Paper


We propose in this paper a new enhancement algorithm dedicated to dark computed tomography (CT) scan based on discrete wavelet transform with singular value decomposition (DWT–SVD) followed by adaptive gamma correction (AGC). Discrete wavelet transform (DWT) is considered to decompose the input dark CT image in four sub-bands. Singular value decomposition (SVD) is used in order to compute the corresponding singular value matrix of low–low (LL) sub-band image. The enhanced LL sub-band is determined by scaling the singular value matrix of original LL sub-band by an adequate correction factor, followed by inverse SVD. For a further contrast improvement, the new enhanced LL sub-band image is processed using an AGC algorithm. Finally, the obtained LL sub-band image undergoes inverse DWT together with the unprocessed sub-bands to generate the final enhanced image. This proposed method has the advantage of being fully automatic and could be applied for dark input images with either low or moderate contrast. Different dark CT images are considered to compare the performance of our proposed method to three other enhancement techniques using both objective and subjective assessments. Simulation results show that our proposed algorithm consistently produces good contrast enhancement, with best brightness and edges details conservation and with minimum added distortions to the enhanced CT images.


Dark CT scan Contrast enhancement SVD AGC 



The author would like to thank the Deanship of Scientific Research at Majmaah University for funding this work under Project No. 37/109.


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Fathi Kallel
    • 1
    • 2
  • Mouna Sahnoun
    • 1
  • Ahmed Ben Hamida
    • 1
  • Khalil Chtourou
    • 3
  1. 1.Laboratory of Advanced Technologies for Medicine and Signal, National Engineering School of SfaxUniversity of SfaxSfaxTunisia
  2. 2.Electrical Engineering Department, College of EngineeringMajmaah UniversityMajmaahSaudi Arabia
  3. 3.Department of Nuclear MedicineCHU Habib BourguibaSfaxTunisia

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