The article presents a method to accurately estimate implied volatility and transition probability density functions in financial markets. By using a Dupire's model and a variance surface with TPS approximation, the researchers were able to construct these functions even with missing data. The linear programming problem they developed resulted in accurate market implied volatilities. The process is detailed with helpful figures and algorithms, showing how they overcame obstacles to achieve their final results.