PERBANDINGAN TRANSFORMASI WAVELET DISKRIT DAN TRANSFORMASI WAVELET STASIONER UNTUK DENOISING CITRA - Ahmad Khairul Umam; Irma Wulandari; Agung Teguh Setyadi; Hasnah Aulia Zahra; Khansa Nadhif Shafa (Universitas Negeri Surabaya, 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.