In this course, I introduce the elements of information theory required to understand why Uniformization or Gaussianization of density functions and noise in the system are key for the transmission of visual information. This knowledge is the basis of our long-standing agenda on developing invertible transforms for uniformization (SPCA, PPA, DRR) and Gaussianization (RBIG), and our research to calibrate neural noise in the visual system and Divisive Normalization models.