DeepAI
Log In Sign Up

Speckles-Training-Based Denoising Convolutional Neural Network Ghost Imaging

04/07/2021
by   Yuchen He, et al.
0

Ghost imaging (GI) has been paid attention gradually because of its lens-less imaging capability, turbulence-free imaging and high detection sensitivity. However, low image quality and slow imaging speed restrict the application process of GI. In this paper, we propose a improved GI method based on Denoising Convolutional Neural Networks (DnCNN). Inspired by the corresponding between input (noisy image) and output (residual image) in DnCNN, we construct the mapping between speckles sequence and the corresponding noise distribution in GI through training. Then, the same speckles sequence is employed to illuminate unknown targets, and a de-noising target image will be obtained. The proposed method can be regarded as a general method for GI. Under two sampling rates, extensive experiments are carried out to compare with traditional GI method (basic correlation and compressed sensing) and DnCNN method on three data sets. Moreover, we set up a physical GI experiment system to verify the proposed method. The results show that the proposed method achieves promising performance.

READ FULL TEXT

page 1

page 5

page 7

page 8

03/25/2021

Generative-Adversarial-Networks-based Ghost Recognition

Nowadays, target recognition technique plays an important role in many f...
06/08/2020

Photoacoustic Microscopy with Sparse Data Enabled by Convolutional Neural Networks for Fast Imaging

Photoacoustic microscopy (PAM) has been a promising biomedical imaging t...
09/28/2020

Noise Variance Estimation Using Asymptotic Residual in Compressed Sensing

In compressed sensing, the measurement is usually contaminated by additi...
04/19/2020

Deep Learning Improves Contrast in Low-Fluence Photoacoustic Imaging

Low fluence illumination sources can facilitate clinical transition of p...
05/29/2021

Compressed Sensing for Photoacoustic Computed Tomography Using an Untrained Neural Network

Photoacoustic (PA) computed tomography (PACT) shows great potentials in ...
11/29/2018

Iterative Residual CNNs for Burst Photography Applications

Modern inexpensive imaging sensors suffer from inherent hardware constra...
01/02/2019

Optical Fringe Patterns Filtering Based on Multi-Stage Convolution Neural Network

Optical fringe patterns are often contaminated by speckle noise, making ...