This article presents a fast parallel lossless technique and a lossy image compression technique for 16-bit single-channel images. Nowadays, such techniques are “a must” in robotics and other areas where several depth cameras are used. Since many of these algorithms need to be run in lowprofile hardware, the should be very fast and customizable. As depth images represent surfaces, the idea is to split the image into a set of polynomial functions that each describes a part of the surface. The algorithm herein proposed can achieve similar —or better— compression rate and specially high speed rates than existing techniques. It has the potential of being fully parallelizable and running on many cores. This feature makes it specially useful for handling and streaming multiple cameras. The algorithm is assessed in different situations and hardware. Its implementation is rather simple and is carried out with LIDAR captured images. Therefore, this work is accompanied by an open implementation in C++.