Aiming at the characteristic of salt & pepper noise, the switch salt & pepper noise suppression algorithm for noise points data restoration based on LS-SVR (least square support vector machines regression) is presented. First, the max-min operator is used to differentiate the noise at the filter windows center, if the center is not the windows extremum, they will output naturally, otherwise they will be judged as noise and divide windows into center corrupted points and multi-corrupted points. The well data approach ability is utilized to fit the curved surface for windows. It realized efficient restoration of data corrupted and reduced the data points damage for miscarriage of justice as noise. To improve the arithmetic operation speed, it constructed the two type LS-SVR convolution mask based on the filtering strategy and LS-SVR characteristic, training process of LS-SVR is turned into simple weighted summation operation which increased the algorithmic practicability. Experiments show that the proposed algorithm has better detailed protecting ability and better removing noise ability.