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A low-cost very large scale integration (VLSI) implementation of real-time correction of barrel distortion for video-endoscopic images is presented in this paper. The correcting mathematical model is based on least-squares estimation. To decrease the computing complexity, we use an odd-order polynomial to approximate the back-mapping expansion polynomial. By algebraic transformation, the approximated polynomial becomes a monomial form which can be solved by Hornor's algorithm. With the iterative characteristic of Hornor's algorithm, the hardware cost and memory requirement can be conserved by time multiplexed design. In addition, a simplified architecture of the linear interpolation is used to reduce more computing resource and silicon area. The VLSI architecture of this paper contains 13.9-K gates by using a 0.18 μm CMOS process. Compared with some existing distortion correction techniques, this paper reduces at least 69% hardware cost and 75% memory requirement.