Depth-image-based-rendering　(DIBR)　techniques　are　significant　for　3D　video　applications,　e.g.,　3D　television　and　free　viewpoint　video　(FVV).　Unfortunately,　the　DIBR-synthesized　image　suffers　from　various　distortions,　which　induce　an　annoying　viewing　experience　for　the　entire　FVV.　Proposing　a　quality　evaluator　for　DIBR-synthesized　images　is　fundamental　for　the　design　of　perceptual　friendly　FVV　systems.　Since　the　associated　reference　image　is　usually　not　accessible,　full-reference　(FR)　methods　cannot　be　directly　applied　for　quality　evaluation　of　the　synthesized　image.　In　addition,　most　traditional　no-reference　(NR)　methods　fail　to　effectively　measure　the　specifically　DIBR-related　distortions.　In　this　paper,　we　propose　a　novel　NR　quality　evaluation　method　accounting　for　two　categories　of　DIBR-related　distortions,　i.e.,　geometric　distortions　and　sharpness.　First,　the　disoccluded　regions,　as　one　of　the　most　obvious　geometric　distortions,　are　captured　by　analyzing　local　similarity.　Then,　another　typical　geometric　distortion　(i.e.,　stretching)　is　detected　and　measured　by　calculating　the　similarity　between　it　and　its　equal-size　adjacent　region.　Second,　considering　the　property　of　scale　invariance,　the　global　sharpness　is　measured　as　the　distance　between　the　distorted　image　and　its　downsampled　version.　Finally,　the　perceptual　quality　is　estimated　by　linearly　pooling　the　scores　of　two　geometric　distortions　and　sharpness　together.　Experimental　results　verify　the　superiority　of　the　proposed　method　over　the　prevailing　FR　and　NR　metrics.　More　specifically,　it　is　superior　to　all　competing　methods　except　APT　in　terms　of　effectiveness,　but　greatly　outmatches　APT　in　terms　of　implementation　time.