Research On Reciprocal Cell Restoration Oriented To Remote Sensing Image

Reciprocal cell restoration was based on single frame of satellite image. The restoration was transformed image into frequency domain. The superposition part of the frequency spectrum was removed between adjacent grids by proposed method. The conventional restorations were combined with the reciprocal cell to denoise and deblur. Finally, the clear image was obtained. This dissertation carried out a further study on the reciprocal cell theory and its restorations of remote image. Study has been done in the following aspects:Firstly, the cause of the aliasing on remote sensing image was analyzed. In addition, the distortion of aliasing was tested quantificationally on images. The distortion of aliasing was special for the Wiener and TV(Total Variation) combined with reciprocal cell. The extent for the range of aliasing was defined through specific example images.From the viewpoint of MTF(Modulation Transfer Function) Compensation, the physical meaning of reciprocal cell was a low-passed filter. It trends to Shannon filter and retained figure smooth at the same time.Besides, the deconvolution of reciprocal cell was studied. There exsited phenomena in the proceeding of deconvolution, such as colour noise and colour aliasing. And the concept of colour aliasing was raised creatively here in the first time. The formula of colour aliasing was derived unprecedentedly. Whereafter, the manifestation of colour noise and colour aliasing were brought forth on frequency domain.Moreover, the restoration of wavelet combined with reciprocal cell was proposed. The mathematic model was formulated with aliasing. The hybrid of Wavelet- Reciprocal cell could dealias, denoise and deblur, which was better than restorations on frequency domain.Finally, the subpixel technique and its interpolations were studied. The wavelet interpolation of subpixel images and median filter was brought forward. After further study, the complex wavelet of subpixel technic was raised. The method was the hybrid between complex wavelet interpolation and denoising of dual-trees complex wavelet. Thereafter, test showed this algorithm could receive better results than the wavelet interpolation.