Real-time disparity estimation requires real-time rectification which involves solving the models of lens distortions, image translations and rotations. Low complexity look-up-table based rectification algorithms usually require an external memory to store large look-up-tables. In this chapter, we present an implementation of the look-up-table based approach which compresses the rectification information to fit the look-up-table into the on-chip memory of a Virtex-5 FPGA. First, a very low complexity compressed look-up-table based rectification algorithm (CLUTR) and its real-time hardware are presented. The implemented CLUTR hardware rectifies stereo images with moderate lens distortion and camera misalignment. Moreover, an enhanced version of the compressed look-up-table based rectification algorithm (E-CLUTR) and its novel real-time hardware are presented. E-CLUTR solves more extreme camera alignment and distortion issues than CLUTR while maintaining the low complexity architecture.