Skip to main navigation Skip to search Skip to main content

Image degradation characteristics and restoration based on regularization for diffractive imaging

  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Original languageEnglish
Pages (from-to)226-238
Number of pages13
JournalInfrared Physics and Technology
Volume86
DOIs
StatePublished - Nov 2017

Keywords

  • Diffractive imaging system
  • Dispersion correcting
  • Image's detail preserving
  • MTF enhancing
  • Multi-objective improvement
  • Noise suppressing
  • Space-variant image restoration

Fingerprint

Dive into the research topics of 'Image degradation characteristics and restoration based on regularization for diffractive imaging'. Together they form a unique fingerprint.

Cite this