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

<table class="table-group" id="tab9"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Algorithm</td><td class="align_center">ReconNet</td><td class="align_center">SCDA</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">The number of network parameters (K)</td><td class="align_center">2900</td><td class="align_center">806</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The number of network parameters for 10 images (the measurement rate is 0.20).</div>

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tab9

Table 9

Table 9: [Retracted] The Analysis about Compressed Sensing Reconstruction Algorithm Based on Machine Learning Applied in Interference Multispectral Images 

Table 9 | [Retracted] The Analysis about Compressed Sensing Reconstruction Algorithm Based on Machine Learning Applied in Interference Multispectral Images 