In pipeline nondestructive testing， the traditional gray-scale visualization method of magnetic flux leakage （MFL） data has the disadvantages of large display delay and low identification degree for the defect curve view and the gray-scale view， respectively. To solve these problems， an self-adaptive sliding window based gray feature enhancement method for MFL data is proposed. Firstly， according to the characteristics of MFL data， the unequal classification label is established and the down-sampling ratio is set to realize the down-sampling display of the original MFL data. Then， according to the preprocessed MFL data， the self-adaptive sliding window and gray value compensation algorithm are designed to realize the local gray mapping of MFL data. Finally， an self-adaptive gray mapping method is designed based on MFL data classification label to get a clear gray view of MFL data. Some comparative experiments are conducted to verify the advance and effectiveness of the proposed method.