arXiv Open Access 2015

Compressive Sensing of Large-Scale Images: An Assumption-Free Approach

Wei-Jie Liang Gang-Xuan Lin Chun-Shien Lu

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Abstrak

Cost-efficient compressive sensing of big media data with fast reconstructed high-quality results is very challenging. In this paper, we propose a new large-scale image compressive sensing method, composed of operator-based strategy in the context of fixed point continuation method and weighted LASSO with tree structure sparsity pattern. The main characteristic of our method is free from any assumptions and restrictions. The feasibility of our method is verified via simulations and comparisons with state-of-the-art algorithms.

Topik & Kata Kunci

cs.MM cs.IT

Penulis (3)

Wei-Jie Liang

Gang-Xuan Lin

Chun-Shien Lu

Format Sitasi

APA MLA BibTeX

Liang, W., Lin, G., Lu, C. (2015). Compressive Sensing of Large-Scale Images: An Assumption-Free Approach. https://arxiv.org/abs/1505.05407

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Informasi Jurnal

Tahun Terbit: 2015
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓