Motion　estimation　refers　to　estimating　2-D　motion　vector　field　of　the　scene　or　object　according　to　temporal　information　redundancy　in　a　clipped　video.　Because　of　its　simplicity　and　efficiency,　block-based　motion　estimation　has　recently　been　widely　used.　This　paper　proposes　a　hybrid　method　for　combining　spatial　prediction　with　the　CDS　algorithm.　If　the　motion　of　the　current　block　is　similar　to　that　of　its　neighbor　blocks,　we　choose　the　best　candidate　block　from　the　neighbor　blocks　and　use　its　motion　vector　to　form　an　initial　estimate　for　the　current　block.　The　neighbor　block　whose　motion　vector　yields　the　minimum　block　distortion　is　called　the　best　candidate　block.　The　true　motion　vector　is　then　obtained　by　comparing　the　search　points　of　SDSP　centered　at　the　initial　estimate.　If　the　current　block　is　not　correlated　with　its　spatial　neighbors,　we　search　for　the　motion　vector　from　the　origin　of　the　search　window　using　the　CDS　algorithm.　Experimental　results　show　that　the　proposed　algorithm　achieves　a　better　tradeoff　between　search　speed　and　accuracy　for　super　resolution　restoration　than　N3SS,　DS,　HEXBS,　CDS,　and　CDHS.