Plates　of　aluminum　have　the　advantages　of　low　density,　high　strength　and　corrosion　resistance,　and　are　widely　used　in　aviation,　aerospace,　shipbuilding　and　other　industrial　fields.　Performing　defect　detection　and　structural　health　monitoring　is　of　great　significance　for　ensuring　the　health　of　facilities　and　maintaining　normal　production　and　use.　Lamb　waves　can　propagate　long　distances　with　low　attenuation　in　metal　plates　to　achieve　long-distance　non-destructive　testing.　Laser　detection　technology　has　been　applied　in　the　field　of　non-destructive　testing　and　has　the　advantages　of　high　spatial　resolution　and　non-contact.　In　this　study,　Full　laser-based　Lamb　waves　array　imaging　based　on　the　two-dimensional　multiple　signal　classification　algorithm　is　proposed　to　locate　and　image　defects　in　the　aluminum　plate.　A　full　laser　ultrasonic　detection　system　is　used　to　excite　and　receive　laser-based　Lamb　wave　signals.　The　array　is　cross-shaped　and　is　used　to　collect　the　data.　Laser-based　Lamb　wave　signals　with　wideband　and　low　time　domain　resolution　are　processed　by　continuous　wavelet　transform　to　obtain　a　narrowband　signal　with　certain　central　frequency.　Finally,　the　two-dimensional　multiple　signal　classification　algorithm　is　used　to　realize　the　localization　and　imaging　of　defects　in　the　aluminum　plate.　©　2020　IEEE.