Carlos A. Sing-Long1,2, Cristian A. Tejos1,2, Pablo Irarrazaval1,2
1Departamento de Ingenieria Electrica, Pontificia Universidad Catolica de Chile, Santiago, R.M., Chile; 2Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, R.M., Chile
Compressed Sensing allows reconstructing signals, if they are sparse in some representation, from some of its Fourier coefficients. The reconstruction conditions are stated in terms of the support size of the signal. Since it is generally unknown, it is impossible to determine if there are reconstruction errors due to high undersampling rates. Our work introduces a modified fixed-point solver for a continuous approximation of the l0-norm and an index which shows high correlation with the reconstruction error. This index does not need any a priori information and may be used to determine if the undersampling rate needs to be reduced.