The objective of this mini-project is to Recover a full image from a small number of sampled pixels (compressed sensing). Although the primary goal of this project is to understand and explore the application of regularized. In the process of recovering image pixel using regularized regression, we will explore different concepts and their understanding as following: Understanding how regression can be applied in 2D image analysis domain. Understanding of the discrete cosine transforms (DCT) to define an image in a frequency domain. Explore the importance and application of cross validation in model tunning and hyper-parameter selections. Understanding the impact of applying filtering approach such as median filter on reconstructed image Finally, quantitively evaluating the quality of removed image.
