Intravascular Ultrasound (IVUS) strain imaging of the luminal layer in coronary arteries, coined as IVUS palpography, utilizes conventional radiofrequency (RF) signals. The signals, acquired at two different levels of a compressional load, are cross-correlated to obtain the microscopic tissue displacements. The latter can be directly translated into local strain of the vessel wall. However, (apparent) tissue motion due to catheter wiggling reduce signal correlation and result in void strain estimates. To compensate for the motion artifacts in IVUS palpography, a novel method, based on the feature-based scale-space Optical Flow (OF), and classical Block Matching (BM) algorithms were employed. The computed OF vector and BM displacement fields quantify the amount of local tissue misalignment in consecutive frames. Subsequently, the extracted motion pattern is used to realign the signals prior to the cross-correlation analysis, reducing the RF signal decorrelation and increasing the number of valid strain estimates. The advantage of applying the motion compensation algorithms in IVUS palpography was demonstrated in a mid-scale validation study on 14 in-vivo pullbacks. Both methods substantially increase the number of valid strain estimates in the partial and compounded palpograms. The best method, OF, attained a mean relative improvement of 28% and 14%, respectively. Implementation of motion compensation methods boosts the diagnostic value of IVUS palpography.