Pengoptimalan Kecepatan Kompresi Citra Fraktal dengan Menggunakan Jarak Variansi Kuadrat

Authors

DOI:

https://doi.org/10.21831/pythagoras.v20i1.79254

Keywords:

Image compression, fractal, square variance distance, encoding, decoding

Abstract

Kompresi citra fraktal terdiri dari dua tahap utama, yaitu encoding dan decoding. Proses encoding umumnya membutuhkan waktu yang lebih lama karena melibatkan pencocokan antara blok domain dan blok range, sedangkan decoding berlangsung lebih cepat. Untuk meningkatkan efisiensi encoding, metode dengan jarak variansi kuadrat atau root variance distance (SVD) dikembangkan sebagai pendekatan seleksi blok domain yang lebih optimal. Metode ini menghitung perbedaan variansi antara blok domain dan blok range, sehingga hanya blok domain dengan karakteristik variansi tertentu yang dipertimbangkan dalam proses pencocokan. Dengan cara ini, jumlah perbandingan blok dapat dikurangi secara signifikan, sehingga mempercepat proses kompresi. Pengujian menggunakan citra grayscale berukuran 256í—256 piksel menunjukkan bahwa metode ini mampu mempercepat waktu encoding hingga 34 kali lebih cepat dibandingkan metode tanpa variansi, dengan kualitas citra hasil kompresi yang tetap terjaga pada Peak Signal-to-Noise Ratio (PSNR) sebesar 23.0 pada ukuran blok range 8í—8.

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Published

2026-01-23

How to Cite

Sultoni, A. (2026). Pengoptimalan Kecepatan Kompresi Citra Fraktal dengan Menggunakan Jarak Variansi Kuadrat. PYTHAGORAS Jurnal Matematika Dan Pendidikan Matematika, 20(1). https://doi.org/10.21831/pythagoras.v20i1.79254

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Vol. 20 No. 1 (2025)

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