Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent
Figure 6
(a) True dictionary composed of 90 atoms. (b) Part of the total training data. (c)–(f) Learned dictionaries from NMFSC, NN-KSVD, NMF-H, and PCDDL algorithms. The numbers of learned atoms are 77, 72, 86, and 89, respectively. Note that these resulting dictionaries have been realigned to facilitate comparison with the original dictionary.
