Algorithm 1 K-SVD Dictionary Construction18
1:	Initialize J by the discrete cosine transformation matrix
2:	repeat
3:	Find sparse coefficients Λ(λi′s) using any pursuit algorithm.
4:	for j = 1, 2, …, update ji, the j-th column of J, by the following process do
5:	Find the group of vectors that use this atom: ζi: = {i: 1 ≤ i ≤ M, λi(j) ≠ 0}
6:	Compute where Ej: = Q − Σi ≠ j ji ΛiT where ΛiT is the i-th row of Ë
7:	Extract the i-th columns in Ej, where i ∈ ζj, to form $E_j^R$
8:	Apply SVD to get $E_j^R=U\Delta V$
9:	ji is updated with the first column of U
10:	The non-zeros elements in ${\Lambda }_T^j$ is updated with the first column of V × Δ(1,1)
11:	end for
12:	until Convergence criteria is met