Non-Gaussian Linear Mixing Models for Hyperspectral Images

<table>Base <svg height="16.6" id="M222" style="vertical-align:-3.50804pt" version="1.1" viewbox="0 0 48.700001 16.6" width="48.700001" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> values of the chi-square statistic (for testing the multivariate <i>t</i>-distribution) plotted versus <svg height="7.9499998" id="M223" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 7.3000002 7.9499998" width="7.3000002" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,0,0,-.017,.062,7.675)"><path d="M393 379q-9 -16 -28 -29q-15 -10 -23 -2q-19 19 -36 19q-21 0 -52 -38q-57 -72 -82 -126l-40 -197q-23 -3 -75 -18l-7 7q49 196 74 335q7 43 -2 43q-7 0 -30 -14.5t-47 -37.5l-16 23q37 42 82 73t67 31q41 0 15 -113l-11 -50h4q41 71 85 117t77 46q29 0 45 -26
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</svg> (for the Cooke City image).</table>

Journal of Electrical and Computer Engineering

Non-Gaussian Linear Mixing Models for Hyperspectral Images

Figure 16