In this paper, we present a new stereo vision-based system and its efficient hardware implementation for real-time underwater environments exploration throughout 3D sparse reconstruction based on a number of feature points. The proposed underwater 3D shape reconstruction algorithm details are presented. The main concepts and advantages are discussed and comparison with existing systems is performed. In order to achieve real-time video constraints, a hardware implementation of the algorithm is performed using Xilinx System Generator. The pipelined stereo vision system has been implemented using Field Programmable Gate Arrays (FPGA) technology. Both timing constraints and mathematical operations precision have been evaluated in order to validate the proposed hardware implementation of our system. Experimental results show that the proposed system presents high accuracy and execution time performances.