HFM = Hybrid Focusing Metric = the best metric ever

sharpness+compactness was the key so we did the math
wrote our own lovely algorithm
to estimate the correct sound speed combination for skin layers:

input: reconstructed image set I(x,y,c)
output: enhanced estimated image and sound speeds
1. reconstruct image I(x,y) of sound speeds c₁,...c_n.
2. compute sharpness value F_intensity ← I(x,y)
3. compute the normalized histogram of I(x,y)
4. compute mean intensities μ_c(k) μ_g(k) by Otsu's method
5. compute the class variance σ_b²(k)
6. find K such that σ_b²(K) ← σ_b²(k) ∃ K ∈ [0, L]
7. if threshold number ≠ 1 then
K ← (K₁ + K₂ + ... + K_n) / n
end if
8. f(x, y) = 1 for I(x, y) ≥ K
f(x, y) = 0 for I(x, y) < K
9. F_TPC ← sum f(x, y)
10. F_HFM(c₁,...,c_n) = F_intensity / F_TPC
11. return c₁,...,c_n ← max(F_(c1,...,cn))

The main contribution I had on this project is simulating and analyzing data hence the discovery of this new metric as well as literature search.