Algorithm Research Of Super-resolution Reconstruction And Its Application For Underwater Image

Underwater target detecting is an important technique for the development of theocean engineering and exploration,also a significant task of the ocean detecting.Itplays a substantial role not only for the civil economy but also for the nationalsecurity.The formation of the super-resolution underwater image is a significant topicin ocean detecting field.In order to solve the lower-resolution underwater image,theimage super-resolution reconstruction technique is applied to the underwater imageprocessing.For decades,super-resolution reconstruction is a hot topic in image andvideo processing which is theoretically important as well as practically urgent inmany fields.This dissertation focuses on the super-resolution of image and videosequence based on the degraded model of underwater image.And the study is carriedout in the following aspects:(1) The establishment of underwater degraded model.There are two methods arediscussed in this part about establishment of the water PSF.The first method is basedon the theoretic organon.For incoherent illumination situation,abc parameters ofwater transmission system are measured and its PSF can be modeled in an analyticalformula,while the PSF can not be achieved when in coherent illumination conditions,which is still in theory research stage.This will be the further research work in thisdissertation.The second means for modeling is experimental method.On theconsideration that the acquired data underwater is determined by water PSF and noise,so the first step is data filtering to compress noise and then model the PSF matrix withthe filtered data.For both incoherent and coherent illumination environment,theirunderwater PSFs are achieved,which can be used for future image restoration.(2) Image preprocessing:in the view of illumination absorption by water andforward dispersion which cause image contrast degradation,and backward scatteringwhich blurs image,also noise caused by photoelectricity,three preprocessing methodsare proposed herein,(a) inverse filtering method to overcome image blurring on thebasis of water PSF;(b) image intensity adjustment with the precondition of imagetexture protection.(c) Nonlinear filter methods based on noise attribute.Thepreprocessing is to offer good SNR image for later super-resolution reconstruction. (3) Super-resolution reconstruction for single frame.Three aspect contents aredebated herein,(a) for the sake that outlier image pixels can cause great aftermath forimage reconstruction,the PCNN simplified model ICM is adopted to detect noneGaussian outlier image pixels;(b)According to the characteristics of these outlierpixels,an improved extremurn-median nonlinear filter is proposed to remove thesenone Gaussian outlier image pixels;(c) traditional interpolation methods are improved,in which high and low frequency image areas are interpolated with differentalgorithm.(4) Super-resolution reconstruction for multi-frames.There are two parts for thistopic:the first part is about image registration in frequency domain,which is on thebasis that none overlapped low frequency parts contain high frequency informationand the registration is carried out in frequency domain.The second part introduces theimproved Keren registration algorithm in spatial domain and improved steepestdescent method for MLE reconstruction.The former improved method is to overcomethe error caused by Taylor series extended in small angle in Keren method,and theimprovement is based on affine transformation with 6 parameters,which can achievebetter registration results than old method when larger angled shift occurred forrigid-body;the later improved method offers a new clue of realization in real time forsuper-resolution reconstruction algorithm.