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Retinex-Centered Contrast Enhancement Method for Histopathology Images with Weighted CLAHE

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Abstract

In the field of pathological testing, it has been discovered that the visibility of histopathological images is poor in the majority of cases due to insufficient brightness and contrast. Improving their quality and preserving their natural characteristics are critical requirements for initial identification and subsequent analysis. The paper described a novel image enhancement technique for improving color histopathology image contrast based on retinex theory and local contrast adjustment. Initially, a multiscale retinex with adaptive weighting is proposed, which first processes the V channel in the HSV color space and then combines several single-scale retinex (SSR) resulting outputs in such a way that the weight corresponding to each SSR scale is determined adaptively from the value channel image, depending on the strength and weakness of the various SSR outputs. Following that, the new weighted contrast limited adaptive histogram equalization method is used to improve local contrast in the L*a*b* color space's luminosity channel, which enhances local histopathology details by fusing the two CLAHE outputs corresponding to the large and lower clip limits. The presented scheme is visually and quantitatively evaluated in comparison with other existing algorithms. Visual and quantitative results on a variety of test images show that the proposed method outperforms all other conventional approaches and produces higher-quality histopathology images, which is especially useful for disease inspection and diagnosis.

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Availability of data and material

The datasets generated and/or analyzed during the present study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Karishma Rao & Manu Bansal

  2. Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Gagandeep Kaur

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  1. Karishma Rao
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  2. Manu Bansal
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  3. Gagandeep Kaur
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Correspondence to Karishma Rao.

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Rao, K., Bansal, M. & Kaur, G. Retinex-Centered Contrast Enhancement Method for Histopathology Images with Weighted CLAHE. Arab J Sci Eng 47, 13781–13798 (2022). https://doi.org/10.1007/s13369-021-06421-w

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