블록 단위 재평가 및 광역 오프셋 초기화를 이용한 장면 기반 불균일보정 보완
Scene-based Nonuniformity Correction Complemented by Block Reweighting and Global Offset Initialization
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초록
In this paper, the block reweighting and global offset initialization methods are proposed to complement the improved IRLMS algorithm which is the effective algorithm in registration based SBNUC algorithm. Proposed block weighting method reweights the error map whose abnormal data are excluded. The global offset initialization method compensates the global nonuniformity initially. The ordinary registration based SBNUC algorithm is hard to compensate global nonuniformity because of low scene motion. We employ the proposed methods to improved IRLMS algorithm, and apply it to real-world infrared raw image stream. The result shows that new implementation provides 3.5~4.0dB higher PSNR and convergence speed 1.5 faster then the improved IRLMS algorithm.
Abstract
In this paper, the block reweighting and global offset initialization methods are proposed to complement the improved IRLMS algorithm which is the effective algorithm in registration based SBNUC algorithm. Proposed block weighting method reweights the error map whose abnormal data are excluded. The global offset initialization method compensates the global nonuniformity initially. The ordinary registration based SBNUC algorithm is hard to compensate global nonuniformity because of low scene motion. We employ the proposed methods to improved IRLMS algorithm, and apply it to real-world infrared raw image stream. The result shows that new implementation provides 3.5~4.0dB higher PSNR and convergence speed 1.5 faster then the improved IRLMS algorithm.
참고문헌 (17)
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