PENINGKATAN KUALITAS CITRA BAWAH AIR BERBASIS ALGORITMA FUSION DENGAN KESEIMBANGAN WARNA, OPTIMALISASI KONTRAS, DAN PEREGANGAN HISTOGRAM

  • Suharyanto Suharyanto Universitas Bina Sarana Informatika
  • Frieyadie Frieyadie Universitas Nusa Mandiri https://orcid.org/0000-0002-8282-0672
  • Sandra Jamu Kuryanti Universitas Bina Sarana Informatika
Keywords: White Balancing, Grey World, CLAHE, Multi-scale fusion, Weight maps, Dehazing, Gaussian filtering.

Abstract

Para peneliti saat ini memberikan perhatian yang cukup besar terhadap obyek citra bawah air, kebutuhan akan aplikasi pengamatan citra bawah air memiliki peran yang sangat penting dalam mengidentifikasi objek, pemantauan kehidupan spesies, deteksi kebocoran pipa minyak atau gas, pemantauan polusi, dan sebagainya. Degradasi citra bawah air merupakan fenomena atmosfer yang merupakan hasil dari hamburan dan penyerapan cahaya. Kami menggunakan satu gambar terdistorsi untuk mendapatkan kontras yang ditingkatkan dan versi koreksi warna dari gambar aslinya. Selanjutnya menghilangkan distorsi dan meningkatkan visibilitas objek dalam gambar dengan menerapkan peta bobot, hal ini dapat dicapai dengan menerapkan penyeimbangan warna putih, kemudian penajaman menggunakan gaussian filtering dilakukan untuk, meningkatkan tampilan visual. pada setiap input yang di proses. Langkah terakhir dilakukan menaikan nilai kontras dengan koreksi peregangan kontras yang dibatasi utuk meningkatkan warna keabuan dan uuntuk menhjilangkan efek noise yang berlebihan pada latar belakang obyek gambar. Hasil penelitian evaluasi menggunakan fitur Root Mean Squared Error (RMSE), dan Peak Signal-to-Noise Ratio (PSNR) dan kami bandingkan dengan metode CLAHE. Hasil evaluasi menunjukkan  peningkatan PNSR yang signifikan kualitas citra yg di perbaiki menggunakan algoritma kombinasi dibanding dengan menggunakan metode CLAHE sebagaimana yang kami paparkan dalam bagian hasil penelitian.

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References

A C, S., & C A, P. (2020). Underwater Image Enhancement by Multiscale Fusion Technique and Dehazing. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1–6. https://doi.org/10.1109/ICCCNT49239.2020.9225421

Ancuti, C. O., Ancuti, C., De Vleeschouwer, C., & Bekaert, P. (2018). Color Balance and Fusion for Underwater Image Enhancement. IEEE Transactions on Image Processing, 27(1), 379–393. https://doi.org/10.1109/TIP.2017.2759252

Hitam, M. S., Awalludin, E. A., Jawahir Hj Wan Yussof, W. N., & Bachok, Z. (2013). Mixture contrast limited adaptive histogram equalization for underwater image enhancement. International Conference on Computer Applications Technology, ICCAT 2013. https://doi.org/10.1109/ICCAT.2013.6522017

Hj Wan Yussof, W. N. J., Hitam, M. S., Awalludin, E. A., & Bachok, Z. (2013). Histogram Equalization Technique on Combined Color Models for Underwater Image Enhancement. International Journal of Interactive Digital Media, 1(1), 1–6. www.ijidm.org

Horé, A., & Ziou, D. (2010). Image quality metrics: PSNR vs. SSIM. Proceedings - International Conference on Pattern Recognition, 2366–2369. https://doi.org/10.1109/ICPR.2010.579

Li, C., Guo, C., Ren, W., Cong, R., Hou, J., Kwong, S., & Tao, D. (2019). An Underwater Image Enhancement Benchmark Dataset and Beyond. 1–12. http://arxiv.org/abs/1901.05495

Luo, W., Duan, S., & Zheng, J. (2021). Underwater image restoration and enhancement based on a fusion algorithm with color balance, contrast optimization and histogram stretching. IEEE Access, 9. https://doi.org/10.1109/ACCESS.2021.3060947

Mehra, R. (2016). Estimation of the Image Quality under Different Distortions. International Journal Of Engineering And Computer Science, 5(17291), 17291–17296. https://doi.org/10.18535/ijecs/v5i7.20

Mishra, A., Gupta, M., & Sharma, P. (2018). Enhancement of Underwater Images using Improved CLAHE. 2018 International Conference on Advanced Computation and Telecommunication (ICACAT), 1–6. https://doi.org/10.1109/ICACAT.2018.8933665

Nurtantio Andono, P., Eddy Purnama, I. K., & Hariadi, M. (2013). Underwater image enhancement using adaptive filtering for enhanced sift-based image matching. Journal of Theoretical and Applied Information Technology, 52(3), 273–280.

Sanila, K. H., Balakrishnan, A. A., & Supriya, M. H. (2019). Underwater Image Enhancement Using White Balance, USM and CLHE. 2019 International Symposium on Ocean Technology (SYMPOL), 106–116. https://doi.org/10.1109/SYMPOL48207.2019.9005301

Singh, R., & Biswas, M. (2016). Adaptive histogram equalization based fusion technique for hazy underwater image enhancement. 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 1–5. https://doi.org/10.1109/ICCIC.2016.7919711

Subah, S. S., Islam, M. A., & Islam, M. M. (2019). Underwater Image Enhancement Based on Fusion Technique via Color Correction and Illumination Adjustment. 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), 1–5. https://doi.org/10.1109/ICASERT.2019.8934573

Suharyanto, Frieyadie, K. (2021). Laporan Akhir Penelitian Mandiri Analisis Perbaikan Citra Bawah Air 2021. 1.

Suharyanto, F. (2020). Analisis komparasi perbaikan kualitas citra bawah air berbasis kontras pemerataan histogram. Inti Nusa Mandiri, 15(1), 95–102. https://doi.org/10.33480/inti.v15i1.1501

Sujitha, A. C., & Prajith, C. A. (2020). Underwater Image Enhancement by Multiscale Fusion Technique and Dehazing. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1–6. https://doi.org/10.1109/ICCCNT49239.2020.9225421

Tao, Y., Dong, L., & Xu, W. (2020). A Novel Two-Step Strategy Based on White-Balancing and Fusion for Underwater Image Enhancement. IEEE Access, 8, 217651–217670. https://doi.org/10.1109/ACCESS.2020.3040505

Published
2021-08-08
How to Cite
Suharyanto, S., Frieyadie, F., & Kuryanti, S. (2021). PENINGKATAN KUALITAS CITRA BAWAH AIR BERBASIS ALGORITMA FUSION DENGAN KESEIMBANGAN WARNA, OPTIMALISASI KONTRAS, DAN PEREGANGAN HISTOGRAM. INTI Nusa Mandiri, 16(1), 31-38. https://doi.org/10.33480/inti.v16i1.2286

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