Spatial-frequency domain imaging coupled with frequency optimization for estimating optical properties of two-layered food and agricultural products

Abstract Understanding optical properties of food and agricultural products is essential to apply optical techniques for quality and safety assessment. This research was aimed at optimizing the frequency region through an inverse algorithm for better quantification of the optical absorption (μa) and reduced scattering (μs′) coefficients of two-layered food and agricultural products from spatial-frequency domain reflectance. The frequency region, defined by start and end frequencies, was first optimized for parameter estimations of the first and second layers, respectively. Estimation accuracies were then validated by comparing with the conventional all-at-once method through Monte Carlo simulations. On average, accuracies for estimating μa1, μa2 and μs2′ by using the optimized frequency region were improved by 52.9%, 63.0% and 62.1%, respectively, compared to the results by using fixed frequency region before optimization. No improvement for the estimated μs1′ was found because its mean absolute error was already very low (2.4%) and well within the acceptable level. Experimental results for two-layered solid phantoms and liquid milk samples in the wavelengths of 650–830 nm further validated the effectiveness of stepwise method with the optimized frequency region. Finally, the stepwise method, coupled with the optimized frequency region was used to estimate the optical properties of skin and flesh of apples for four cultivars (i.e., Delicious, Golden Delicious, Jonagold and Red Rome). The results were compared with those obtained using the single integrating sphere technique, followed with a discussion on the optical property discrepancies obtained by these two methods.