From early years, Electrocardiogram (ECG) signal plays an important role in the primary diagnosis and analysis of heart diseases. Good quality ECG is utilized by the physicians for interpretation and identification of physiological and pathological phenomena. De-noising is to reduce noise level while the signal degradation is minimized. As noise is usually corrupted with signals, de-noising is important and usual in many applications. Suppressing a noise of ECG effectively is a classical problem. In this paper, types of noises that affect the ECG signals and the existing methods like Wavelet Transform, Adaptive Filtering, Neural Networks, Singular value Decomposition, Fuzzy Logic and FIR Filtering for ECG de-noising is presented.