Compressive　light　field　photography　has　gained　a　significant　research　interest　during　the　past　years.　One　important　problem　in　light　field　images　is　the　effective　representation　of　the　structures.　In　this　paper,　based　on　collaborative　projection　and　sparse　dictionary,　we　propose　a　light　field　reconstruction　optimization　scheme　for　compressive　light　field　photography.　By　utilizing　the　special　structural　feature　of　high　correlations　among　light　field　views,　an　optimized　structured　dictionary　is　proposed,　which　is　more　memory　and　time　efficient　compared　with　general　sparse　dictionary.　Furthermore,　we　propose　the　corresponding　structured　dictionary　learning　model　and　efficient　algorithm　to　train　the　optimized　dictionary　with　fixed　projection.　Simulation　results　on　light　field　data　set　demonstrate　the　effectiveness　of　our　optimizing　scheme　in　terms　of　reconstruction　quality　compared　with　general　sparse　dictionary.