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1715116 Vol 9 · Issue 9 Download Paper

Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization

Aaswitha Myneni Harini Vunnam Nagendra Vemparala Kalyan Konda Chandana Kotha

Subject area: Science,Engineering and Technology  ·  Area of research: Satellite Image Processing

DOI: 10.64388/IREV9I9-1715116

Abstract

Satellite images generally have low contrast, non- uniform illumination, and structural details visibility suffer from atmospheric interference, sensor limitations, and different acquisition conditions, which greatly hamper visual analysis and interpretation. In this paper, a Contrast-Guided Adaptive Multiscale Retinex (CG-AMSR) approach is proposed for satellite image visualization enhancement. Based on the theory of Multiscale Retinex with New Kernel (MSRNK), the authors of the method adaptive contrast guidance to control enhancement strength locally while retaining natural appearance. Multiscale processing is used for balancing global illumination correction and local detail enhancement, and an improved kernel formulation is implemented to stabilize illumination normalization without generating halo artifacts or saturation effects. Moreover, contrast-aware weighting and normalization techniques are used to preserve structural integrity and maintain the overall tonal balance. The authors assess the proposed model's effectiveness through visual examination and by using objective quality indices, such as entropy, PSNR, SSIM, and contrast enhancement index. The proposed approach outperforms the other three baseline methods quantitatively and qualitatively in terms of contrast enhancement as well as detail preservation. Also, the resultant images from the proposed method show more visual clarity and popularity. As such, the method can be considered as a viable candidate for handling real-world satellite image analysis and visualization problems.

Keywords

Satellite Image Enhancement, Multiscale Retinex, Contrast-Guided Enhancement, Illumination Normalization, ImageVisualization,MSRNK, Adaptive Contrast Enhancement

References

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[10] Tejas, K. R., et al. "Image Recognition and Enhancement using Multi Scale Retinex and Histogram Equalization." 2023 2nd International Conference for Innovation in Technology (INOCON). IEEE, 2023.

[11] Rajalakhmi, B., Geethika, P., & Kolalapudi, R. S. (2023, January). Image Recognition and Enhancement Using Multi- Scale Retinex and Histogram Equalization. In 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE) (pp. 444-447). IEEE.

[12] Li, Jiaxin, and Zhi Ou. "Remote Sensing Image Processing of Ecological Environment Monitoring Based on Multi-scale Retinex Algorithm." 2023 2nd International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME). IEEE, 2023.

[13] Han, Feixiang, et al. "Deep-Space Background Low-Light Image Enhancement Method Based on Multi-Image Fusion." Applied Sciences 15.9 (2025): 4837.

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How to cite this paper

Aaswitha Myneni, Harini Vunnam, Nagendra Vemparala, Kalyan Konda, Chandana Kotha "Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1088-1099 https://doi.org/10.64388/IREV9I9-1715116
Aaswitha Myneni, Harini Vunnam, Nagendra Vemparala, Kalyan Konda, Chandana Kotha "Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026, doi: https://doi.org/10.64388/IREV9I9-1715116
Aaswitha Myneni, Harini Vunnam, Nagendra Vemparala, Kalyan Konda, Chandana Kotha (2026). Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization. Iconic Research And Engineering Journals, 9(9). doi: https://doi.org/10.64388/IREV9I9-1715116
Aaswitha Myneni, Harini Vunnam, Nagendra Vemparala, Kalyan Konda, Chandana Kotha "Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization" Iconic Research And Engineering Journals, vol. 9, no. 9, Mar. 2026. Crossref, https://doi.org/10.64388/IREV9I9-1715116
@article{1715116,
      author = {Aaswitha Myneni, Harini Vunnam, Nagendra Vemparala, Kalyan Konda, Chandana Kotha},
      title = {Contrast-Guided Adaptive Multiscale Retinex for Enhanced Satellite Image Visualization},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {1088-1099},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715116.pdf},
      abstract = {Satellite images generally have low contrast, non- uniform illumination, and structural details visibility suffer from atmospheric interference, sensor limitations, and different acquisition conditions, which greatly hamper visual analysis and interpretation. In this paper, a Contrast-Guided Adaptive Multiscale Retinex (CG-AMSR) approach is proposed for satellite image visualization enhancement. Based on the theory of Multiscale Retinex with New Kernel (MSRNK), the authors of the method adaptive contrast guidance to control enhancement strength locally while retaining natural appearance. Multiscale processing is used for balancing global illumination correction and local detail enhancement, and an improved kernel formulation is implemented to stabilize illumination normalization without generating halo artifacts or saturation effects. Moreover, contrast-aware weighting and normalization techniques are used to preserve structural integrity and maintain the overall tonal balance. The authors assess the proposed model's effectiveness through visual examination and by using objective quality indices, such as entropy, PSNR, SSIM, and contrast enhancement index. The proposed approach outperforms the other three baseline methods quantitatively and qualitatively in terms of contrast enhancement as well as detail preservation. Also, the resultant images from the proposed method show more visual clarity and popularity. As such, the method can be considered as a viable candidate for handling real-world satellite image analysis and visualization problems.},
      keywords = {Satellite Image Enhancement, Multiscale Retinex, Contrast-Guided Enhancement, Illumination Normalization, ImageVisualization,MSRNK, Adaptive Contrast Enhancement},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715116}
  }