Ultrasound exams are a popular tool for image acquisition in day-to-day medicine, since it is a noninvasive, safe and cheap procedure. However, speckle noise is intrinsic to any ultrasound exam, and it is responsible for image quality degradation and for hindering its interpretation by doctors and patients alike, while also impairing the accuracy of post processing computational methods, such as classification, reconstruction, tissue characterization and segmentation, among others. Hence, smoothing or denoising methods that preserves the observed content core attributes are essential for those processes. Defined as a multiplicative noise, following non-Gaussian statistics and as strongly correlated, its solution today is still a matter of debates and research. In this work, several 2D filters that aim to smooth or remove speckle noise along with qualitative methods to evaluate their performances and means of choosing their best parameters are presented.