이해근 박사 Infrared Image Deconvolution논문 Sensors에 게재
2023.03.13 13:19
본 연구실 졸업생인 이해근 박사가 연구한 “Infrared Image Deconvolution Considering Fixed Pattern Noise” 제목의 논문이 Sensors (Impact factor : 3.847, Rank : Q2)에 게재가 확정되었다. 본 연구는 이해근 박사(1저자)와 강문기 교수(교신저자)가 진행하였다.
Abstract
As the demand for thermal information increases in industrial fields, numerous studies have focused on enhancing the quality of infrared images. Previous studies have attempted to independently overcome one of the two main degradations of infrared images, fixed pattern noise (FPN) and blurring artifacts, neglecting the other problems, to reduce the complexity of the problems. However, this is infeasible for real-world infrared images, where two degradations coexist and influence each other. Herein, we propose an infrared image deconvolution algorithm that jointly considers FPN and blurring artifacts in a single framework. First, an infrared linear degradation model that incorporates a series of degradations of the thermal information acquisition system is derived. Subsequently, based on the investigation of the visual characteristics of the column FPN, a strategy to precisely estimate FPN components is developed, even in the presence of random noise. Finally, a non-blind image deconvolution scheme is proposed by analyzing the distinctive gradient statistics of infrared images compared with those of visible-band images. The superiority of the proposed algorithm is experimentally verified by removing both artifacts. Based on the results, the derived infrared image deconvolution framework successfully reflects a real infrared imaging system.
