As　a　novel　molecular　imaging　technology,　bioluminescence　tomography　(BLT)　has　become　an　important　tool　for　biomedical　research　in　recent　years,　which　can　perform　a　quantitative　reconstruction　of　an　internal　light　source　distribution　with　the　scattered　and　transmitted　bioluminescent　signals　measured　on　the　external　surface　of　a　small　animal.　However,　BLT　is　severely　ill-posed　because　of　complex　photon　propagation　in　the　biological　tissue　and　limited　boundary　measured　data　with　noise.　Therefore,　sufficient　a　priori　knowledge　should　be　fused　for　the　uniqueness　and　stability　of　BLT　solution.　Permissible　source　region　strategy　and　spectrally　resolved　measurements　are　two　kinds　of　a　priori　knowledge　commonly　used　in　BLT　reconstruction.　This　paper　compares　their　performance　with　simulation　and　in　vivo　heterogeneous　mouse　experiments.　In　order　to　improve　the　efficiency　of　large-scale　source　restoration,　this　paper　introduces　an　efficient　iterative　shrinkage　thresholding　method　that　not　only　has　faster　convergence　rate　but　also　has　better　reconstruction　accuracy　than　the　modified　Newton-type　optimization　approach.　Finally,　a　discussion　of　these　two　kinds　of　a　priori　knowledge　is　given　based　on　the　comparison　results.