The Research On Model-based Image Restoration And Super-resolution Reconstruction For Underwater Laser Imaging

Underwater imaging is widely used in ocean, river and lake exploration, but it is affected by properties of water and the optics including lenses and sensors. Image restoration methods can help to eliminate the blur caused by absorption and scattering; however, the resolution is still limited or even degraded, and the restoration methods are needed to be improved. Considering all the aspects of image formation, this dissertation studies and proposes various image restoration and super-resolution reconstruction methods.The dissertation introduces the underwater range-gated laser imaging system, gives a detailed block diagram of the experimental equipment and experimental results; reviews and analyzes the similarities and differences of several classic point-spread models which determine the needs of modeling. By calculating the three components of light irradiance reaching the detector, based on linear transmission theory, an underwater imaging model suitable for the range-gated imaging system considering the gated time was established in this study including laser beam propagation affected by absorption and scattering, the effects of underwater turbulence and the diffraction limit of sensors. The model-derived modulation transfer function (MTF) and point spread function (PSF) are applied for the theoretical basis of underwater image processing.The dissertation proposes and tests an edge based hybrid block denoising method and applies it as the preprocessing module before the restoration and super-resolution reconstruction. As there exists no ideal or reference image for underwater imaging system, blind, objective quality metrics are chosen for evaluating the performance of the PSF-based restoration and reconstruction methods respectively.Based on the MTF and PSF derived by the imaging model, PSF-based semi-blind restoration is verified by its performance in a structured light detection system. MTF-based restoration methods in frequency domain and PSF-based restoration methods in time domain are tested by their performance in our underwater range-gated imaging system. Super-resolution reconstruction methods operated by single and multiple frames are introduced in the underwater range-gated imaging system, performances of which show adequate accuracy and feasibility. The PSF-based reconstruction methods in time domain are also tested by their performance in our underwater range-gated imaging system.In order to process the experimental imagery to a best possible level, image restoration and super-resolution reconstruction techniques are combined with the point spread function (PSF) of underwater range-gated imaging system under the maximum a posteriori (MAP) framework, performance of which shows superiority compared to other methods. Edge detection are performed and proved that the restoration and super-resolution reconstruction methods proposed by this dissertation can effectively enhance the resolution and quality of underwater range-gated imaging.