ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing
Type
Conference PaperAuthors
Zhang, JianGhanem, Bernard

KAUST Department
Visual Computing Center (VCC)Electrical Engineering Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2018-12-18Online Publication Date
2018-12-18Print Publication Date
2018-06Permanent link to this record
http://hdl.handle.net/10754/656532
Metadata
Show full item recordAbstract
With the aim of developing a fast yet accurate algorithm for compressive sensing (CS) reconstruction of natural images, we combine in this paper the merits of two existing categories of CS methods: the structure insights of traditional optimization-based methods and the speed of recent network-based ones. Specifically, we propose a novel structured deep network, dubbed ISTA-Net, which is inspired by the Iterative Shrinkage-Thresholding Algorithm (ISTA) for optimizing a general norm CS reconstruction model. To cast ISTA into deep network form, we develop an effective strategy to solve the proximal mapping associated with the sparsity-inducing regularizer using nonlinear transforms. All the parameters in ISTA-Net (e.g. nonlinear transforms, shrinkage thresholds, step sizes, etc.) are learned end-to-end, rather than being hand-crafted. Moreover, considering that the residuals of natural images are more compressible, an enhanced version of ISTA-Net in the residual domain, dubbed ISTA-Net+, is derived to further improve CS reconstruction. Extensive CS experiments demonstrate that the proposed ISTA-Nets outperform existing state-of-the-art optimization-based and network-based CS methods by large margins, while maintaining fast computational speed. Our source codes are available: http://jianzhang.tech/projects/ISTA-Net.Citation
Zhang, J., & Ghanem, B. (2018). ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. doi:10.1109/cvpr.2018.00196Publisher
IEEE Computer SocietyConference/Event name
31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018arXiv
1706.07929Additional Links
https://ieeexplore.ieee.org/document/8578294/ae974a485f413a2113503eed53cd6c53
10.1109/CVPR.2018.00196