[Retracted] The Analysis about Compressed Sensing Reconstruction Algorithm Based on Machine Learning Applied in Interference Multispectral Images

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Algorithm</td><td class="align_center">D-AMP</td><td class="align_center">ReconNet</td><td class="align_center">SCDA</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Time (s)</td><td class="align_center">36.01</td><td class="align_center">0.05</td><td class="align_center">0.04</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The average time required for the reconstruction process (the measurement rate is 0.05).</div>

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tab7

Table 7

Table 7: [Retracted] The Analysis about Compressed Sensing Reconstruction Algorithm Based on Machine Learning Applied in Interference Multispectral Images 

Table 7 | [Retracted] The Analysis about Compressed Sensing Reconstruction Algorithm Based on Machine Learning Applied in Interference Multispectral Images 