For best performance in image compression, wavelet transforms require filters that combine some important properties, such as orthogonality and symmetry. However, in the designing of wavelets this combination is limited because to have these simultaneous properties is not possible, except in the Haar case. The multiwavelet system allows more design options than wavelet, and therefore, several simultaneous characteristics such as: compact support, smoothness, higher order approach, symmetry and orthogonality, among others. Therefore, establishing parameters which allow comparing of scalar wavelets and multiwavelets performance, is a necesity. This paper provides an overview of filter banks, wavelets, multiwavelets, basic principles, and connections between each one, in addition to some experimental results from the compression of test images, comparing each system performance.