The Research Of Single Image Recovery In Fog And Underwater

Images in a scattering medium (such as fog, water and smoke) are inevitably degraded,resulting in blurring details and color distortion as well as poor image contrast.Fog-degraded images and underwater images are both hazed due to the absorption andscattering of the scattering medium. The scattering can be divided into forwardscattering and backscattering, where the forward scattering leads to the light blur ofdetails and the backscattering causes the serious atomization. Image recovery in ascattering medium is highly desired for many applications and gains widely attentionsof the researchers: some researchers aim to solve the problem of increasing imagingrange by improving the equipment performance, which costs too much to be widelyused; some researches develop the image processing techniques to recover the hazeimage, which is considered to be more simple and powerful.Degradation of imaging system in scattering medium is complex; it needs full-fledged prior knowledge on the scattering medium to recover the haze image. Theearlier recovery methods were based on two or more images to obtain more priorknowledge of scattering, others were based on measuring to derive the degradationfunction; these methods cannot effectively solve the existing degraded image forreal-time requirement.In this paper, image recovery methods based on single image which are alsowithout measure of the scattering medium in the real environment are researched; themain work and innovations are listed as follows:1) The blur degradation and the backscattering noise themselves contain a largenumber of information related to the inherent optical properties (IOP) of the scatteringmedium. This paper proposes a multi-layered decomposition of the scattering volumeand models blurring function of a single-layer scattering volume based on manners of the calculus and the physical extremum problem. Supposing the backscattering noiseof each tiny singe-layer is uncorrelated, when the model is integrated to infinite, it canfit the degradation parameters just by the pure backscattering region.2) Since scattering degradation is associated with the depth of object andconcentration of the medium, this paper carried out an actual water environmentalexperiment to analyze the correctness of the multi-layered model on these two aspects.The experiment includes that: comparing the parameters of backscattering noise ofdifferent water; analyzing the depth correlation by images obtained at different rangesin the same water, and finding out the proportional relationship between the real depthand the parameter depth. What’s more, when the depth is known, this multi-layeredmodel can also help to solve the IOP related prior.3）This paper proposes an effective method called propagating deconvolution torecover single image degraded in a scattering medium. Parameters of thedeconvolution algorithm are estimated just from in-situ measurement of the purescattered background from one single image. Two kinds of propagating deconvolutionare used which are linear filter propagating deconvolution and nonlinear totalvariation propagating deconvolution. The results are analyzed and compared with theother two widely used single image dehaze methods.4）Total variation (TV) restoration uses the image TV minimization as theconvergence regularization in the iterations; While traditional linear filter also needs aconvergence criterion in the iterations of propagating deconvolution. This paperresearches several different criteria and come to a conclusion that image entropymaximization is suitable for the fog-degraded images and underwater images whosereference images are not available.