A novel brightness preserving joint histogram equalization technique for contrast enhancement of brain MR images

• Autorzy: Mishro Pranaba K , Agrawal Sanjay , Panda Rutuparna , Abraham Ajith

Identyfikatory

DOI

10.1016/j.bbe.2021.04.003

• Języki publikacji: EN

Abstrakty

EN

Low contrast is a challenging factor in brain magnetic resonance (MR) images due to its structural complexity. Histogram equalization (HE) approach is often used in enhancing the contrast in brain MR images. However, the spatial information is not taken into account in this approach. Further, the problem of preserving structural details while retaining the brightness is also an important concern. To solve these, we suggest a novel stationary wavelet transform based brightness preserving joint histogram equalization (SWT-BPJHE) scheme for brain MR image contrast enhancement. Our contributions are – i) use of SWT to extract the low sub-band wavelength coefficients from the low contrast input image for enhancement, ii) to isolate the high frequency wavelength coefficients from enhancement, retaining the structural details, iii) to preserve brightness. The suggested scheme is experimented with synthetic brain MR images from BrainWeb and clinical images from Howard Whole Atlas databases. The performance is evaluated in terms of several validation indices followed by statistical analysis. The outcomes reveal the superiority of the suggested scheme in comparison to state-of-the-art methods.

Słowa kluczowe

EN

MR image processing; contrast enhancement; Joint histogram equalization

PL

przetwarzanie obrazu MR; poprawa kontrastu; wyrównanie histogramu

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 2
• Strony: 540--553
• Opis fizyczny: Bibliogr. 41 poz., rys., tab., wykr.

Twórcy

autor

Mishro Pranaba K

• Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla, India

autor

Agrawal Sanjay

• Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla, India

autor

Panda Rutuparna

• Department of Electronics & Telecommunication Engineering, VSS University of Technology, Burla, India

autor

Abraham Ajith

• Machine Intelligence Research Labs, Washington, USA

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).