심층 신경망 기반 영상 내 압축 포아송 잡음 제거 기법 및 장치
- 11430090 (2022.08.30)
19MH1500, 5G 기반의 스마트시티 서비스 개발 및 실증,
- A method for removing compressed Poisson noises in an image, based on deep neural networks, may comprise generating a plurality of block-aggregation images by performing block transform on low-frequency components of an input image; obtaining a plurality of restored block-aggregation images by inputting the plurality of block-aggregation images into a first deep neural network; generating a low-band output image from which noises for the low-frequency components are removed by performing inverse block transform on the plurality of restored block-aggregation images; and generating an output image from which compressed Poisson noises are removed by adding the low-band output image to a high-band output image from which noises for high-frequency components of the input image are removed.
- KSP 제안 키워드
- Block Transform, Deep neural network(DNN), Frequency components, High Frequency(HF), Poisson Noise, high-band, high-frequency components, low-band, low-frequency, neural network