ABSTRAKSI: Citra digital merupakan salah satu bentuk citra yang paling mudah dipergunakan dari segi pengiriman sebagai data, pengolahan dan pemrosesan citra itu sendiri. Ketika citra diimplementasikan dalam kehidupan, sering kali dalam proses pengiriman citra, baik melalui satelit maupun melalui kabel, akan mengalami interferensi atau gangguan dari luar yang mengakibatkan citra terkena noise. Dalam tugas akhir ini dilakukan implementasi dan analisis penggunaan metode BayesShrink yang berbasis wavelet untuk mendapatkan threshold yang digunakan dalam proses denoising. Noise yang digunakan adalah additive gaussian noise, impulsive noise dan additive laplacian noise yang akan dibangkitkan melalui suatu noise generator. Dari hasil percobaan yang diperoleh, metode BayesShrink dinilai cukup baik dalam menghilangkan noise, serta diperoleh kesimpulan mengenai proses denoising yang lebih baik antara denosing yang dilakukan pada domain spasial dengan denoising yang dilakukan pada domain frekuensi.Kata Kunci : Wavelet, Threshold, denoising, BayesShrink, Additive Gaussian Noise, Impulsive Noise, Additive Laplacian Noise.ABSTRACT: Digital image is a kind of image that is very easy to used, like for image transmission as data, enhancement and processing. When image is implemented in our life, example in sending process through satelite or near cable, it often happened interference that causing noise into the images. In this final project, it has been implemented and analysed the used of Bayes Shrink method based on wavelet to yield threshold which is used for denoising process. The noise which is used in this final project are additive gaussian noise, impulsive noise and addiviti laplacian noise which is generated by noise generator. From the experimental results obtained, bayes shrink method was considered good in removing noise, as well as the conclusion of the better denoising process between denoising performed on spatial domain and denoising performed in the frequency domain.Keyword: Wavelet, Threshold, denoising, BayesShrink, Additive Gaussian Noise, Impulsive Noise, Additive Laplacian Noise.