The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 우천 시 차량에 장착된 후방 카메라를 통해 획득한 영상에서 부착된 물방울을 제거하는 ER(Error-Reduction) 알고리즘 기반 방법을 제안한다. 모든 ER 알고리즘 기반 방법에는 푸리에 영역 및 객체 영역 제약 조건이 필요하므로 제안된 방법에서는 부착된 물방울 제거를 위해 다음과 같은 두 가지 새로운 제약 조건을 도입합니다. 첫 번째는 획득된 이미지에서 이전 프레임의 푸리에 변환 크기를 대상 프레임의 크기로 활용하는 푸리에 영역 제약입니다. 일반적으로 후방카메라가 넓은 시야각을 위해 어안렌즈로 구성되어 후방카메라 영상이 잔물결처럼 움직이는 물체의 독특한 특성을 갖는다는 점에 착안하여, 제안하는 방법에서는 대상의 푸리에 변환 크기를 가정한다. 프레임과 이전 프레임은 극좌표계에서 동일합니다. 두 번째 제약은 대상 프레임에서 물방울이 부착된 영역의 강도를 활용하는 객체 영역 제약입니다. 구체적으로, 제안된 방법은 후방 카메라 렌즈에 부착된 물방울에 의해 손상되는 강도의 저하 과정을 모델링한다. 제안된 ER 알고리즘은 이러한 새로운 제약 조건을 활용하여 후방 카메라를 통해 얻은 영상에서 부착된 물방울을 제거할 수 있습니다. 제안한 방법의 성능을 검증한 실험 결과를 나타내었다.
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부
Tomoki HIRAMATSU, Takahiro OGAWA, Miki HASEYAMA, "An ER Algorithm-Based Method for Removal of Adherent Water Drops from Images Obtained by a Rear View Camera Mounted on a Vehicle in Rainy Conditions" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 8, pp. 1939-1949, August 2009, doi: 10.1587/transfun.E92.A.1939.
Abstract: In this paper, an ER (Error-Reduction) algorithm-based method for removal of adherent water drops from images obtained by a rear view camera mounted on a vehicle in rainy conditions is proposed. Since Fourier-domain and object-domain constraints are needed for any ER algorithm-based method, the proposed method introduces the following two novel constraints for the removal of adherent water drops. The first one is the Fourier-domain constraint that utilizes the Fourier transform magnitude of the previous frame in the obtained images as that of the target frame. Noting that images obtained by the rear view camera have the unique characteristics of objects moving like ripples because the rear view camera is generally composed of a fish-eye lens for a wide view angle, the proposed method assumes that the Fourier transform magnitudes of the target frame and the previous frame are the same in the polar coordinate system. The second constraint is the object-domain constraint that utilizes intensities in an area of the target frame to which water drops have adhered. Specifically, the proposed method models a deterioration process of intensities that are corrupted by the water drop adhering to the rear view camera lens. By utilizing these novel constraints, the proposed ER algorithm can remove adherent water drops from images obtained by the rear view camera. Experimental results that verify the performance of the proposed method are represented.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1939/_p
부
@ARTICLE{e92-a_8_1939,
author={Tomoki HIRAMATSU, Takahiro OGAWA, Miki HASEYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An ER Algorithm-Based Method for Removal of Adherent Water Drops from Images Obtained by a Rear View Camera Mounted on a Vehicle in Rainy Conditions},
year={2009},
volume={E92-A},
number={8},
pages={1939-1949},
abstract={In this paper, an ER (Error-Reduction) algorithm-based method for removal of adherent water drops from images obtained by a rear view camera mounted on a vehicle in rainy conditions is proposed. Since Fourier-domain and object-domain constraints are needed for any ER algorithm-based method, the proposed method introduces the following two novel constraints for the removal of adherent water drops. The first one is the Fourier-domain constraint that utilizes the Fourier transform magnitude of the previous frame in the obtained images as that of the target frame. Noting that images obtained by the rear view camera have the unique characteristics of objects moving like ripples because the rear view camera is generally composed of a fish-eye lens for a wide view angle, the proposed method assumes that the Fourier transform magnitudes of the target frame and the previous frame are the same in the polar coordinate system. The second constraint is the object-domain constraint that utilizes intensities in an area of the target frame to which water drops have adhered. Specifically, the proposed method models a deterioration process of intensities that are corrupted by the water drop adhering to the rear view camera lens. By utilizing these novel constraints, the proposed ER algorithm can remove adherent water drops from images obtained by the rear view camera. Experimental results that verify the performance of the proposed method are represented.},
keywords={},
doi={10.1587/transfun.E92.A.1939},
ISSN={1745-1337},
month={August},}
부
TY - JOUR
TI - An ER Algorithm-Based Method for Removal of Adherent Water Drops from Images Obtained by a Rear View Camera Mounted on a Vehicle in Rainy Conditions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1939
EP - 1949
AU - Tomoki HIRAMATSU
AU - Takahiro OGAWA
AU - Miki HASEYAMA
PY - 2009
DO - 10.1587/transfun.E92.A.1939
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2009
AB - In this paper, an ER (Error-Reduction) algorithm-based method for removal of adherent water drops from images obtained by a rear view camera mounted on a vehicle in rainy conditions is proposed. Since Fourier-domain and object-domain constraints are needed for any ER algorithm-based method, the proposed method introduces the following two novel constraints for the removal of adherent water drops. The first one is the Fourier-domain constraint that utilizes the Fourier transform magnitude of the previous frame in the obtained images as that of the target frame. Noting that images obtained by the rear view camera have the unique characteristics of objects moving like ripples because the rear view camera is generally composed of a fish-eye lens for a wide view angle, the proposed method assumes that the Fourier transform magnitudes of the target frame and the previous frame are the same in the polar coordinate system. The second constraint is the object-domain constraint that utilizes intensities in an area of the target frame to which water drops have adhered. Specifically, the proposed method models a deterioration process of intensities that are corrupted by the water drop adhering to the rear view camera lens. By utilizing these novel constraints, the proposed ER algorithm can remove adherent water drops from images obtained by the rear view camera. Experimental results that verify the performance of the proposed method are represented.
ER -