Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control

Asim Khwaja, Roland Goecke

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    Abstract

    A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.
    Original languageEnglish
    Title of host publicationProceedings of the 2009 Digital Image Computing: Techniques and Applications
    EditorsHao Shi, Yanchun Zhang, Murk J Bottema, Brian C Lovell, Anthony J Maeder
    Place of PublicationMelbourne, Australia
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages424-430
    Number of pages7
    Volume1
    ISBN (Print)9781424452972
    DOIs
    Publication statusPublished - 2009
    Event2009 Digital Image Computing: Techniques and Applications, DICTA 2009 - Melbourne, Australia
    Duration: 1 Dec 20093 Dec 2009

    Conference

    Conference2009 Digital Image Computing: Techniques and Applications, DICTA 2009
    CountryAustralia
    CityMelbourne
    Period1/12/093/12/09

    Fingerprint

    Gain control
    Color
    Luminance

    Cite this

    Khwaja, A., & Goecke, R. (2009). Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control. In H. Shi, Y. Zhang, M. J. Bottema, B. C. Lovell, & A. J. Maeder (Eds.), Proceedings of the 2009 Digital Image Computing: Techniques and Applications (Vol. 1, pp. 424-430). Melbourne, Australia: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DICTA.2009.75
    Khwaja, Asim ; Goecke, Roland. / Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control. Proceedings of the 2009 Digital Image Computing: Techniques and Applications. editor / Hao Shi ; Yanchun Zhang ; Murk J Bottema ; Brian C Lovell ; Anthony J Maeder. Vol. 1 Melbourne, Australia : IEEE, Institute of Electrical and Electronics Engineers, 2009. pp. 424-430
    @inproceedings{96d0ef63309e483bbbe9f8469ca30379,
    title = "Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control",
    abstract = "A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.",
    author = "Asim Khwaja and Roland Goecke",
    year = "2009",
    doi = "10.1109/DICTA.2009.75",
    language = "English",
    isbn = "9781424452972",
    volume = "1",
    pages = "424--430",
    editor = "Hao Shi and Yanchun Zhang and Bottema, {Murk J} and Lovell, {Brian C} and Maeder, {Anthony J}",
    booktitle = "Proceedings of the 2009 Digital Image Computing: Techniques and Applications",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

    }

    Khwaja, A & Goecke, R 2009, Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control. in H Shi, Y Zhang, MJ Bottema, BC Lovell & AJ Maeder (eds), Proceedings of the 2009 Digital Image Computing: Techniques and Applications. vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Melbourne, Australia, pp. 424-430, 2009 Digital Image Computing: Techniques and Applications, DICTA 2009, Melbourne, Australia, 1/12/09. https://doi.org/10.1109/DICTA.2009.75

    Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control. / Khwaja, Asim; Goecke, Roland.

    Proceedings of the 2009 Digital Image Computing: Techniques and Applications. ed. / Hao Shi; Yanchun Zhang; Murk J Bottema; Brian C Lovell; Anthony J Maeder. Vol. 1 Melbourne, Australia : IEEE, Institute of Electrical and Electronics Engineers, 2009. p. 424-430.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    TY - GEN

    T1 - Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control

    AU - Khwaja, Asim

    AU - Goecke, Roland

    PY - 2009

    Y1 - 2009

    N2 - A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.

    AB - A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.

    U2 - 10.1109/DICTA.2009.75

    DO - 10.1109/DICTA.2009.75

    M3 - Conference contribution

    SN - 9781424452972

    VL - 1

    SP - 424

    EP - 430

    BT - Proceedings of the 2009 Digital Image Computing: Techniques and Applications

    A2 - Shi, Hao

    A2 - Zhang, Yanchun

    A2 - Bottema, Murk J

    A2 - Lovell, Brian C

    A2 - Maeder, Anthony J

    PB - IEEE, Institute of Electrical and Electronics Engineers

    CY - Melbourne, Australia

    ER -

    Khwaja A, Goecke R. Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control. In Shi H, Zhang Y, Bottema MJ, Lovell BC, Maeder AJ, editors, Proceedings of the 2009 Digital Image Computing: Techniques and Applications. Vol. 1. Melbourne, Australia: IEEE, Institute of Electrical and Electronics Engineers. 2009. p. 424-430 https://doi.org/10.1109/DICTA.2009.75