Mr. Lintao Peng Profile

Lintao Peng

at Beijing Institute of Technology

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 4 January 2023 Presentation + Paper

Large-scale single-pixel imaging via deep learning

Siyu Xie, Lintao Peng, Liheng Bian

Proceedings Volume 12317, 1231703 (2023) https://doi.org/10.1117/12.2643014

KEYWORDS: Computer programming, Transformers, Image restoration, Image quality, Feature extraction, Sensors, Image resolution, Reconstruction algorithms, Modulation, Convolution

Read Abstract +

Single-pixel imaging uses a single-pixel detector to capture all photons emitted from the two-dimensional scene, and then calculates and reconstructs the two-dimensional target scene image from the one-dimensional measurement data through single-pixel reconstruction methods (such as linear superposition, compressed sensing or deep learning) based on the one-dimensional acquisition data and the corresponding illumination coding. Compared with traditional cameras, single-pixel imaging has the advantages of high signal-to-noise ratio and wide spectrum. Due to these advantages, single-pixel imaging has been widely used in multispectral imaging. However, the traditional single-pixel image reconstruction methods have some disadvantages, such as low resolution, huge time consuming and poor reconstruction quality. In this paper, we propose a single-pixel image reconstruction method based on neural network. Compared with the traditional single-pixel image reconstruction method, this method has better reconstruction quality at lower sampling rate. Specifically, in this model, we first use a small optimized-patterns to simulate a single-pixel camera to sample the image to obtain the measured values, and then extract multi-channel high-dimensional semantic features from the sampled values through a high-dimensional semantic feature extraction network. Then, the multi-scale residual network module is used to construct the feature pyramid up-sampling module to up sample the high-dimensional semantic features. In the training process, the network parameters and pattern are jointly optimized to obtain the optimal network model and pattern. With the help of large-scale and pre-training, our reconstructed image has higher resolution, shorter reconstruction time and better reconstruction quality.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years