Infrared blind spectral deconvolution with low-rank sparse regularization for small object tracking

•Low-rank sparse regularization approach is employed analyze the sparsity of the infrared spectrum.•The rank of data matrix can distinguish the difference between the high-resolution spectrum and low-resolution one.•Our low-rank approach outperforms other competing methods in terms of accuracy by the experimental results.