ScreenedPoissonSolver

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1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. def apply(imageFFT: libcog.ComplexField, gradient: libcog.VectorField, lambda: Float): libcog.ComplexField

   

   Integrate a gradient field subject to the constraint of matching a reference image field as closely as possible.

   Integrate a gradient field subject to the constraint of matching a reference image field as closely as possible. Since this is impossible in general, there is a tradeoff term, lambda, which allows one to balance fidelity to the reference image (larger lambda) and the gradient (smaller lambda).

   imageFFT

   The "periodized" FFT of the reference image field which we want to match as best we can. See the paper "Periodic plus Smooth Image Decomposition," Journal of Mathematical Imaging and Vision, vol 39:2, pp. 161-179, 2011, for a description of the periodic FFT.

   gradient

   The desired gradient field to be integrated.

   lambda

   Tradeoff between fidelity to image (larger value) and integrated gradient (smaller value).

   returns

   Fourier transform of image which best satisfies the given constraints.

5. final def asInstanceOf[T0]: T0

   

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6. def clone(): AnyRef

   

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7. final def eq(arg0: AnyRef): Boolean

   

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8. def equals(arg0: Any): Boolean

   

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9. def finalize(): Unit

   

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10. final def getClass(): Class[_]

    

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11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. def isPowerOf2(value: Float): Boolean

    

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    Logarithm

14. def log2(value: Float): Float

    

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15. final def ne(arg0: AnyRef): Boolean

    

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16. final def notify(): Unit

    

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17. final def notifyAll(): Unit

    

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18. def roundDownPowerOf2(value: Float): Int

    

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19. def roundUpPowerOf2(value: Float): Int

    

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20. final def synchronized[T0](arg0: ⇒ T0): T0

    

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21. def toString(): String

    

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22. final def wait(): Unit

    

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23. final def wait(arg0: Long, arg1: Int): Unit

    

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24. final def wait(arg0: Long): Unit

    

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