Implementasi dan Analisi Image Scalling Menggunakan Bilinier Interpolation pada Citra Kendaraan
DOI:
https://doi.org/10.70340/jirsi.v4i3.235Keywords:
Digital image processing, bilinear interpolation, image scaling, PSNR, MSE, Visual StudioAbstract
Digital image processing is an essential area in computer science, particularly in manipulating and transforming images for analysis and visualization purposes. One of the fundamental techniques is image scaling, which involves enlarging or reducing the dimensions of an imageThe tests indicate that extreme downscaling leads to a significant decrease in image quality, reflected by lower PSNR and higher MSE. In contrast, moderate upscaling tends to preserve more visual quality, although it cannot enhance image details beyond the original resolution. In conclusion, the bilinear interpolation method can be effectively applied for image scaling in light to moderate scenarios. The evaluation using PSNR and MSE provides a clear quantitative insight into image degradation caused by scaling. This application can serve as a foundation for further development in image processing systems, such as object detection, vehicle classification, or visual surveillance systems.
Downloads
References
Arif, M., & Pratama, F. (2022). Optimized image scaling techniques for object detection pre-processing. Jurnal Teknologi Informasi dan Ilmu Komputer, 9(2), 123–129
Dewi, S. H., & Nugroho, R. A. (2021). Interpolasi citra digital menggunakan metode bilinear dan bicubic untuk perbesaran citra wajah. In Seminar Nasional Teknologi dan Rekayasa (SENTRA) (pp. 45–50).
Putra, A. M., Handayani, L., & Suryani, T. (2022). Tinjauan teknik pre-processing dalam sistem pengenalan pola citra digital. Jurnal Teknologi dan Sistem Komputer, 10(2), 165–172
Munir, R. (2021). Operasi-operasi Dasar Pengolahan Citra. Online] https://informatika. stei. itb. ac. id/~ rinaldi. munir/Citra/2020-2021/05-Operasi-dasar-pengolahan-citra-2021. pdf (Diakses pada 18 Desember 2022).
Kurniawan, B., & Ananda, A. Y. (2023). Analisis pengaruh scaling citra kendaraan terhadap hasil segmentasi dan deteksi pelat nomor. Jurnal Pengolahan Citra Digital, 5(3), 210–218.
Putri, S. N., Prasetyo, R. B., & Yuniarti, R. D. (2024). Studi implementasi bilinear interpolation pada pre-processing sistem klasifikasi kendaraan ringan dan berat. Jurnal Teknologi dan Sistem Komputer (JTSiskom), 12(1), 78–85.
Novandi, T. A., Pratama, A. H., & Rachman, M. (2021). Comparative study of image scaling algorithms for real-time applications. International Journal of Image Processing, 13(4), 102–108.
Sari, P., Akbar, M. F., & Rinaldi, A. (2022). Evaluasi performa interpolasi bilinear dan nearest neighbor pada perubahan ukuran citra. Jurnal RESTI, 6(2), 145–150.
Kurniawan, E., Park, Y., & Lee, S. (2022). Noise-Resistant Demosaicing with Deep Image Prior Network and Random RGBW Color Filter Array. Sensors, 22(5), 1767.
Setiawan, I. R., Fanani, A. Z., Surname, G. N., & Purwanto, P. (2023, February). Optimization of the Use of Artificial Neural Network Models for Accuracy Data Measurement Palm Oil Production Prediction Rate. In 2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) (pp. 732-737). IEEE.
Setiawan, R., Cahyana, R., & Hakim, P. (2021). Implementasi Konsep Behaviorally Anchor Rating Scale pada Sistem Informasi Penilaian Kinerja Karyawan Berbasis Web. Jurnal Algoritma, 18(2), 562-573.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Fahmi Ramadhan

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.