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http://dx.doi.org/10.7236/JIIBC.2018.18.2.117

Image Reconstruction Using Poisson Model Screened from Image Gradient  

Kim, Yong-Gil (Dept.of computer Security, Chosun college of science & technology)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.18, no.2, 2018 , pp. 117-123 More about this Journal
Abstract
In this study, we suggest a fast image reconstruction scheme using Poisson equation from image gradient domain. In this approach, using the Poisson equation, a guided vector field is created by employing source and target images within a selected region at the first step. Next, the guided vector is used in generating the result image. We analyze the problem of reconstructing a two-dimensional function that approximates a set of desired gradients and a data term. The joined data and gradients are able to work like modifying the image gradients while staying close to the original image. Starting with this formulation, we have a screened Poisson equation known in physics. This equation leads to an efficient solution to the problem in FFT domain. It represents the spatial filters that solve the two-dimensional screened Poisson model and shows gradient scaling to be a well-defined sharpen filter that generalizes Laplace sharpening. We demonstrate the results using a discrete cosine transformation based this Poisson model.
Keywords
Image reconstruction; Poisson equation; Image gradient; FFT; DCT;
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