TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Neural-network-based Impulse Noise Removal Using Group-based Weighted Couple Sparse Representation |
| 영문제목(English Title) |
Neural-network-based Impulse Noise Removal Using Group-based Weighted Couple Sparse Representation |
| 저자(Author) |
Yongwoo Lee
Toan Duc Bui
Jitae Shin
Byung Tae Oh
|
| 원문수록처(Citation) |
VOL 12 NO. 08 PP. 3873 ~ 3887 (2018. 08) |
한글내용
(Korean Abstract) |
In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.
|
영문내용
(English Abstract) |
|
| 키워드(Keyword) |
Neural network
noise detector
denoising
impulse noise
sparse representation
|
| 파일첨부 |
PDF 다운로드
|
