Search Algorithms for Block-Matching in Motion Estimation

Interframe predictive coding is used to eliminate the large amount of temporal and spatial redundancy that exists in video sequences and helps in compressing them. In conventional predictive coding the difference between the current frame and the predicted frame (based on the previous frame) is coded and transmitted. The better the prediction, the smaller the error and hence the transmission bit rate. If a scene is still, then a good prediction for a particular pel in the current frame is the same pel in the previous frame and the error is zero. However, when there is motion in a sequence, then a pel on the same part of the moving object is a better prediction for the current pel. The use of the knowledge of the displacement of an object in successive frames is called Motion Compensation. There are a large number of motion compensation algorithms for interframe predictive coding. In this study, however, we have focused only on one class of such algorithms, called the Block Matching Algorithms. These algorithms estimate the amount of motion on a block by block basis, i.e. for each block in the current frame, a block from the previous frame is found, that is said to match this block based on a certain criterion. There are a number of criteria to evaluate the "goodness" of a match and some of them are: 1. Cross Correlation Function 2. Pel Difference Classification (PDC) 3. Mean Absolute Difference 4. Mean Squared Difference 5. Integral Projection