Depth　coding　in　depth-based　3D　video　is　unique　in　that　its　quality　is　measured　by　view　synthesis　distortion　(VSD)　rather　than　the　depth　distortion　itself,　which　further　complicates　the　coding　optimization　as　the　VSD　is　related　to　quality　of　both　the　associated　depth　and　texture　videos.　In　this　paper,　an　efficient　VSD　estimation　scheme　is　developed　to　measure　the　effect　of　depth　errors　on　the　VSD　for　a　block　given　its　depth　distortion　in　mean-squared　error.　Unlike　other　relevant　VSD　models　which　involve　computationally　intensive　parameter　training　or　Fourier　transform,　the　proposed　scheme　is　free　of　parameter　training　while　taking　advantage　of　integer　4×4　discrete　Cosine　transform　to　replace　Fourier　transform,　thus　well　saving　computational　cost　and　diminishing　sensitivity　to　training　dataset　of　video.　The　proposed　scheme　is　then　incorporated　on　the　coding　unit　basis　into　the　rate-distortion　optimization　for　depth　coding　optimization,　coupled　with　adapting　quantization　parameter　accordingly　to　accommodate　local　effect　of　the　depth　errors　on　the　VSD.　Experimental　results　show　that　our　solution　obtains　better　results　in　depth　coding　than　three　testing　solutions,　on　the　platform　of　H.264/AVC　reference　software　JM16.0.　Benefiting　from　the　efficiency　of　the　VSD　estimation,　low　coding　complexity　is　obtained　as　well.　The　proposed　solution　is　further　evaluated　on　the　reference　software　HTM13.0　of　the　latest　3D-HEVC　standard,　exhibiting　better　and　comparable　results　compared　against　the　HTM　codec　with　the　view　synthesis　optimization　disabled　and　enabled,　respectively.　IEEE