Summary: Wavelets, which are used to separate data into different components, have many applications. Steganography, one such application, is a form of secret communication where the existence of a message is concealed. Methods for applying univariate and bivariate wavelets to steganography include embedding messages into the insignificant wavelet coefficients of decomposed signals and images. Recomposing then creates stego-objects that appear unaltered from the original cover-objects. First demonstrated is a technique for hiding messages in strings of data with linear trends using the univariate Daubechies \(D_{4}\) wavelets. Then, after developing the bivariate Haar wavelets and filters, a unique process of decomposing and recomposing an image in greyscale in order to implement steganography will be illustrated.