Super-resolution (SR) video processing method with reduced block artifacts using conventional block-matching algorithm (BMA) is proposed. To get high-quality SR results, accurate motion vectors are necessary in registration process. For real-time applications, block-based motion estimators are widely used, which show block-based motion errors if their motion vectors are employed for the registration. Incorrectly registered pixels due to the block-based motion errors limit the image quality improvement of the SR processing and even degrade the results by causing block artifacts. To reduce the artifacts from the inaccurately registered pixels, a weighting function using three-dimensional confidence measure is proposed in this paper. The measure uses spatial and inter-channel analysis to suppress the weight on incorrectly registered pixels during the SR process. Motion-compensated pixel differences and motion vector variances between previous and current frames are utilized for spatial analysis, and motion vector variance with constant acceleration model and pixel difference variances through LR frames are used for inter-channel analysis. Experimental results show significantly improved results in error regions keeping enhanced quality with accurately registered pixels, when motion vectors are found by conventional BMAs.