Bilateral　filtering　has　been　adopted　for　edge-preserving　image　smoothing　and　achieved　the　state-of-the-art　performance.　Most　of　the　existing　bilateral　filters　(BFs),　however,　focus　on　accelerating　brute-force　implementation　but　not　on　smoothing　quality.　In　this　letter,　we　propose　a　two-pass　(TP)　BF,　TP-based　BF,　and　an　adaptive　control　scheme　of　range　kernels　for　noise-invariant　edge-preserving　image　smoothing.　Specifically,　the　TP-based　BF　is　composed　of　two　bilateral　filtering　operations,　which　are,　respectively,　in　charge　of　coarse　context　extraction　and　fine　structure　refinement.　The　control　scheme　of　range　kernels　guides　the　TP　bilateral　mechanism　to　eliminate　first　high-frequency　noisy　pixels　and　then　explore　contribution　between　pixels　from　clean　contexts.　Experimental　results　on　four　aerial-imagery　benchmark　data　sets　show　that　our　TP-based　BF　outperforms　the　existing　BFs　in　terms　of　both　feature-　and　gradient-aware　measures.