Anti-interference Computational Ghost Imaging with Pink Noise Speckle Patterns

Abstract

We propose a computational ghost imaging scheme using customized pink noise speckle pattern illumination. By modulating the spatial frequency amplitude of the speckles, we generate speckle patterns with a significant positive spatial correlation. We experimentally reconstruct images using our synthesized speckle patterns in the presence of a variety of noise sources and pattern distortion and shown it is robust to noise interference. The results are compared with the use of standard white noise speckle patterns. We show that our method gives good image qualities under different noise interference situations while the traditional way fails. The proposed scheme promises potential applications in underwater, dynamic, and moving target computational ghost imaging.

7 pages, 6 figures

References in corpus (5)

• Hadamard single-pixel imaging versus Fourier single-pixel imaging
• Lensless ghost imaging with true thermal light
• Compressive adaptive computational ghost imaging
• Circumventing the optical diffraction limit with customized speckles
• Computational Ghost Imaging

Cited by in corpus (5)

• Tailoring 3D Speckle Statistics
• 0.8% Nyquist computational ghost imaging via non-experimental deep learning
• Sub-Nyquist computational ghost imaging with orthonormalized colored noise pattern
• Optimizing Ghost Imaging via Analysis and Design of Speckle Patterns
• True image construction in quantum-secured single-pixel imaging under spoofing attack