PERBANDINGAN TRANSFORMASI WAVELET DISKRIT DAN TRANSFORMASI WAVELET STASIONER UNTUK DENOISING CITRA

Ahmad Khairul Umam (Politeknik Elektronika Negeri Surabaya)
Irma Wulandari (Politeknik Elektronika Negeri Surabaya)
Agung Teguh Setyadi (Politeknik Elektronika Negeri Surabaya)
Hasnah Aulia Zahra (Politeknik Elektronika Negeri Surabaya)
Khansa Nadhif Shafa (Politeknik Elektronika Negeri Surabaya)

MATHunesa: Jurnal Ilmiah Matematika
Vol. 13 No. 2 (2025)

The wavelet transform is an improvement of the Fourier transform. Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) are part of the wavelet transform. DWT and SWT can be used to reduce noise in images. In this research, DWT and SWT methods are compared for image denoising process. The PSNR value and computation time for level 1 and 2 wavelets are compared. A grayscale test image of Lena and the cat measuring 512×512 pixels are used. We use Haar, Daubechies, biorthogonal, symlets, and coiflets wavelets. From this research results, the highest PSNR value is for the SWT method. As for the fastest computation time, it is all for DWT method.