This　paper　reports　the　improvement　of　the　image　quality　during　the　fusion　of　remote　sensing　images　by　minimizing　a　novel　energy　function.　First,　by　introducing　a　gradient　constraint　term　in　the　energy　function,　the　spatial　information　of　the　panchromatic　image　is　transferred　to　the　fused　results.　Second,　the　spectral　information　of　the　multispectral　image　is　preserved　by　importing　a　kernel　function　to　the　data　fitting　term　in　the　energy　function.　Finally,　an　objective　parameter　selection　method　based　on　data　envelopment　analysis　(DEA)　is　proposed　to　integrate　state-of-the-art　image　quality　metrics.　Visual　perception　measurement　and　selected　fusion　metrics　are　employed　to　evaluate　the　fusion　performance.　Experimental　results　show　that　the　proposed　method　outperforms　other　established　image　fusion　techniques.