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Journal Article
SCENet: Secondary Domain Intercorrelation Enhanced Network for Alleviating Compressed Poisson Noises
- Authors
- Seok Bong Yoo, Mikyong Han
- Issue Date
- 2019-04
- Citation
- Sensors, v.19, no.8, pp.1-13
- ISSN
- 1424-8220
- Publisher
- MDPI
- Language
- English
- Type
- Journal Article
- Abstract
- In real image coding systems, block-based coding is often applied on images contaminated by camera sensor noises such as Poisson noises, which cause complicated types of noises called compressed Poisson noises. Although many restoration methods have recently been proposed for compressed images, they do not provide satisfactory performance on the challenging compressed Poisson noises. This is mainly due to (i) inaccurate modeling regarding the image degradation, (ii) the signal-dependent noise property, and (iii) the lack of analysis on intercorrelation distortion. In this paper, we focused on the challenging issues in practical image coding systems and propose a compressed Poisson noise reduction scheme based on a secondary domain intercorrelation enhanced network. Specifically, we introduced a compressed Poisson noise corruption model and combined the secondary domain intercorrelation prior with a deep neural network especially designed for signal-dependent compression noise reduction. Experimental results showed that the proposed network is superior to the existing state-of-the-art restoration alternatives on classical images, the LIVE1 dataset, and the SIDD dataset.
- KSP Keywords
- Art restoration, Camera sensor, Challenging issues, Coding system, Deep neural network(DNN), Image coding, Noise reduction(NR), Poisson Noise, Signal-dependent noise, block-based coding, compressed images
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
