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5 방향 그라디언트 손실 함수를 사용한 트랜스포머 기반 단일 영상 비 제거 방법
최진솔(Jinsol Choi),임헌성(Heunseung Lim),최형기(Hyungki Choi),백준기(Joonki Paik) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
In this paper, we propose a novel approach to single image rain removal by incorporating a transformer structure into a U-shaped neural network and implementing a five-direction loss function. Our approach specifically employs a swin-transformer combined with residual and Fourier convolution methods. Beyond conventional x and y directional gradients, we propose a unique technique to eliminate non-components using a five-direction gradient. Experimental results indicate that our method outperforms existing approaches by minimizing information loss and delivering enhanced quality in rain-free images.