Background registration-based filtering for LWIR/MWIR imaging sensors > Defense systems

Research School of Electronics Engineering

Background registration-based filtering for LWIR/MWIR imaging sensors
IR cameras have noises such as dead pixels, lines, and fixed patterns. Non-uniformity correction (NUC), two-point correction (TPC) and scene-based NUC (SBNUC) are studied to reduce noise in IR images, However, these methods still suffer from unfixed(moving) pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis. [1] Kim, Byeong, Min Kim, and You Chae. "Background registration-based adaptive noise filtering of LWIR/MWIR imaging sensors for UAV applications.“, Sensors, 18(1), 2018.

Background registration-based filtering for LWIR/MWIR imaging sensors

IR cameras have noises such as dead pixels, lines, and fixed patterns. Non-uniformity correction (NUC), two-point correction (TPC) and scene-based NUC (SBNUC) are studied to reduce noise in IR images, However, these methods still suffer from unfixed(moving) pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis.

[1] Kim, Byeong, Min Kim, and You Chae. "Background registration-based adaptive noise filtering of LWIR/MWIR imaging sensors for UAV applications.“, Sensors, 18(1), 2018.

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