We present a cofactor-based endmember extraction strategy for estimating green algae area in geostationary ocean color imager multispectral images. Our strategy improves the efficiency of the widely used N-FINDR endmember extraction method from two aspects. First, our strategy exploits the cofactor matrix for searching the largest simplex volume, which just computes matrix inverse and determinant for a small number of times (or even once). This is more efficient than the enumeration of determinants for all pixels in N-FINDR. Second, our strategy empirically obtains optimal endmembers through a few recursive iterations of cofactor matrix updates, contrasting a large number of repetitive volume maximizations with random initializations in N-FINDR. Experimental evaluation in terms of green algae area estimation validates that our strategy achieves the same accuracy as N-FINDR with much more efficiency.