The　rate-distortion　optimization　plays　a　key　role　in　video　coding,　which　aims　to　achieve　a　tradeoff　between　compression　efficiency　and　video　quality　distortion.　The　existing　rate-distortion　optimization　algorithms　mainly　aim　to　eliminate　time　and　space　redundancy,　which　ignore　subjective　perception　of　video　content　and　result　in　a　large　amount　of　perceptual　redundancy　in　video.　To　address　these　issues,　a　rate　distortion　algorithm　based　on　visual　perception　is　proposed　in　this　article.　Firstly,　the　Lagrangian　multiplier　factor　is　obtained　based　on　the　data-driven　just　noticeable　distortion　prediction　mode,　which　is　more　in　line　with　the　perception　of　the　human　eye.　Secondly,　the　Lagrangian　multiplier　weight　coefficient　is　based　on　salient　model.　Finally,　the　fusion　of　two　models　is　applied　to　rate-distortion　optimization,　and　SW-SSIM　is　used　to　evaluate　video　quality　and　achieve　perceptual　video　coding　optimization.　Compared　with　the　third　generation　audio　and　video　coding　standard　algorithm,　experimental　results　show　that　the　proposed　algorithm　reduces　bitrate　by　12.15%　averagely,　and　the　salience　weighted-structural　similarity　index　metric　increases　by　0.004　3.　Furthermore,　the　proposed　algorithm　reduces　the　perceptual　redundancy　in　video　content,　and　improves　the　video　perceptual　quality　and　coding　performance.　©　2022,　Science　Press.　All　right　reserved.