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Hybrid model of alternating least squares and root polynomial technique for color correction

  • Foundation, algebraic, and analytical methods in soft computing
  • Published:
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Abstract

Color correction is an image-altering technique that modifies image color in such a way that it matches a reference image. Many approaches have already been proposed by various researchers; however, those models have been unable to reduce color errors between two images, which results in inefficiency and poor-quality images. This research paper presents an effective and improved color correction model wherein alternate least square (ALS) and root polynomial (RP) are used together. The main objective of the proposed model is to reduce the error between a reference image and a target image to enhance the image quality and make them look realistic. To achieve this objective, the proposed model used the Amsterdam library of object images which contains a picture of single objects captured under various illumination angles and colors. The main contribution of this paper is a hybrid ALS + RP color correction technique, implemented on the dataset image that fixes its color as per the reference image and enhances its quality. The target image is then converted into three color models, i.e., LAB, LUV, and RGB into XYZ format. Finally, the color difference between a reference image and a target image is observed by calculating values for parameters like Mean, median, 95% quantile, and maximum error. The effectiveness of the suggested hybrid color correction approach is assessed and validated in MATLAB software for each color model. Through extensive experiments, it is observed that the proposed hybrid model yields the least errors for the RGB color model. This is followed up by LUV and then LAB, to prove its supremacy over other models.

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Funding

This research received no external funding.

Author information

Authors and Affiliations

  1. Department of Computer Science, Chandigarh University, Gharuan, India

    Geetanjali Babbar & Rohit Bajaj

  2. Department of Computer Science Engineering, CEC, Landran, Punjab, India

    Geetanjali Babbar

  3. University Centre for Research and Development, Chandigarh University, Mohali, India

    Nitin Mittal

  4. School of Engineering, Ajeenkya DY Patil University, Pune, Maharashtra, India

    Shubham Mahajan

  5. Sorbonne Center of Artificial Intelligence, Sorbonne University-Abu Dhabi, 38044, Abu Dhabi, United Arab Emirates

    Raed Abu Zitar

  6. Computer Science Department, Prince Hussein Bin Abdullah Faculty for Information Technology, Al al-Bayt University, 25113, Mafraq, Jordan

    Laith Abualigah

  7. Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, 19328, Amman, Jordan

    Laith Abualigah

  8. Center for Engineering Application & Technology Solutions, Ho Chi Minh City Open University, Ho Chi Minh, Viet Nam

    Laith Abualigah

  9. Faculty of Information Technology, Middle East University, 11831, Amman, Jordan

    Laith Abualigah

  10. Applied science research center, Applied Science Private University, 11931, Amman, Jordan

    Laith Abualigah

  11. School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia

    Laith Abualigah

Authors
  1. Geetanjali Babbar
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  2. Rohit Bajaj
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  3. Nitin Mittal
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  4. Shubham Mahajan
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  5. Raed Abu Zitar
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  6. Laith Abualigah
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Correspondence to Nitin Mittal or Laith Abualigah.

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Babbar, G., Bajaj, R., Mittal, N. et al. Hybrid model of alternating least squares and root polynomial technique for color correction. Soft Comput 27, 4321–4335 (2023). https://doi.org/10.1007/s00500-023-07831-8

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  • DOI: https://doi.org/10.1007/s00500-023-07831-8

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