The underwater robots called Unmanned Underwater Vehicles (UUVs) take over complex and dangerous underwater missions that were previously performed by humans. These vehicles operate in the unknown environments and make their own decisions within the mission based on the readings of the sensors, without any link with a human operator. Independent of the mission, it is critical for the AUVs to be able to avoid submerged obstacles such as cliffs, wrecks, and floating mines. The AUV typically uses underwater imaging sonar that has several drawbacks for obstacle detection purposes, and therefore requires complex image processing algorithms. Due to the imaging sonar limitations, addressing obstacle detection using conventional software algorithms cannot meet an AUV's real-time, low power requirements. A low-power FPGA algorithm for underwater obstacle detection that is based on local image histogram entropy is proposed. The algorithm maintains a real-time reliable performance while meeting the AUV low power budget.