Image　quality　assessment　(IQA)　technology　is　facing　a　new　challenge　due　to　the　large　amount　of　demand　for　high-quality　3-D-synthesized　views　stimulated　by　the　rapid　development　of　virtual　reality　applications.　Since　3-D　synthesis　views　commonly　rely　on　the　depth-image-based　rendering　technology　to　synthesize　virtual　images　(without　reference　images　in　reality　and　containing　geometric　distortion),　only　the　no-reference　(NR)　quality　assessment　method　can　meet　the　requirements.　However,　most　of　the　current　IQA　methods　for　3-D-synthesized　views　are　full-reference　methods.　So　far,　only　one　specialized　NR　IQA　method　for　3-D-synthesized　views　has　been　proposed,　but　its　computation　is　too　expensive.　For　this　reason,　we　have　previously　proposed　a　method　for　extracting　geometric　distortion　regions　using　the　Joint　Photographic　Experts　Group　(JPEG)　image　compression　technology　to　evaluate　image　quality.　In　this　paper,　we　consider　that　although　heavy　JPEG　compression　can　effectively　extract　the　geometric　distortion　area,　it　will　ignore　the　image　quality　degradation　caused　by　other　distortions.　Therefore,　we　have　improved　our　previous　work　to　extract　geometric　distortions　and　non-geometric　distortions　by　high-level　JPEG　compression　and　low-level　JPEG　compression,　respectively.　The　overall　image　quality　score　was　obtained　by　the　fusion　of　the　two　results.　Experiments　indicate　that　the　proposed　blind　quality　model　is　superior　to　modern　full-,　reduced-,　and　no-reference　methods.　Compared　with　our　previous　work,　the　performance　of　the　new　algorithm　has　been　greatly　improved.　At　the　same　time,　compared　with　the　existing　dedicated　NR　IQA　method,　the　performance　is　similar　but　the　calculation　speed　has　obvious　advantages.