Key Technology Of Super-Resolution Image Restoration

Many factors cause blur and corruption of image in imaging process.The purpose Many factors cause blur and corruption of image in imaging process.The purpose of Image Restoration is that it makes the degenerate image similar to the original image. From point of view of Fourier theory, an optical system behaves as a low-pass filter which debars spatial frequency information aboutthe object beyond the diffraction limit cut-off frequency.Now,a lot of Image Restoration methods passes to the cut-off frequency but can't exceed it so that many high frequncy information may be missed.Super-Rosultion Image Restoration (SRIR) can reconstruct information about the object beyond the cut-off frequency when information about the object under the cut-off frequncy is restored.Therefore,image details can be retrived so much that the restored image is greatly close to the original object.In the dissertation,SRIR theory is expounded and its algorithms are summarized.Through the assumption of Poisson of Bayes statistics,then Poisson-ML and Poisson-MAP algorithms are proposed .Through the experiment ,it is found that the two algorithms have strong ability of Image Restoration when the noise is small.For the undersampled image,algorithm of SRIR based on multiframes and Multisensors is proposed.With different and correlate information in muliframes and multisensors fused together,good restoration results are obtained.Through the experiment it is proved that this algorithms can restore the undersampled image.In a word,the theories and means of SRIR is being in process of research.With the study of the SRIR,this means must been in the application abroad.