| Project/Area Number |
17560339
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Communication/Network engineering
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| Research Institution | Osaka University |
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Principal Investigator |
IIGUNI Youji Osaka University, Graduate School of Engineering Science, Professor (80168054)
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| Co-Investigator(Kenkyū-buntansha) |
KAWAMURA Arata Osaka University, Graduate School of Engineering Science, Assistant Professor (60362646)
NAKASHIZUKA Makoto Osaka University, Graduate School of Engineering Science, Associate Professor (10251787)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,470,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥270,000)
Fiscal Year 2007: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2006: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2005: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | image interpolation / matching parameters / radial basis function / DCT / FFT / subpixel accuracy / regularization / high resolution image / サブピクセル精度 / 補間 / ギブス現象 / 量子化誤差 / ナイキスト周波数 / 周波数応答 |
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| Research Abstract |
Image interpolation is a method of reconstructing a continuous or discrete signal from a given digital image. Regularization is one of useful tools for image interpolation due to its excellent interpolation capability. We have proposed fast methods for two image interpolation problems by using the discrete cosine transform (DCT). We have shown that the frequency response of the radial basis function (RBF) interpolation is asymptotically equivalent to the ideal sinc interpolation, and that the RBF interpolation is closer to the ideal sinc interpolation than the cubic spline and Lanczos interpolations. The other problem is the high resolution (HR) image restoration, which restores the HR image from a downsampled low resolution image based on the regularization. We have shown that the downsampling process is expressed in a scalar form in the DCT domain, have derived the analytical solution to the HR restoration problem, hand have developed the fast computation method by using the DCT.
A matching parameter estimation method with subpixel accuracy is derived by using the RBF in-terpolation technique. The estimation method uses the RBF interpolation to generate the continuous images from the digital images taken from the same scene, and then minimizes a nonlinear cost function to estimate translation, rotation, scaling factor, and intensity change between images. The RBF inter-polation can generate accurate continuous images. We have introduced a Gaussian weighting function into the cost function to obtain a local estimate of the matching parameters around a specific region. We have analytically computed a double integral in the cost function, and have reduced the computational complexity of the optimization by noticing that the Gaussian function decays rapidly.
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