Remaps an image to semilog-polar coordinates space

dst = cv.logPolar(src, center, M)
dst = cv.logPolar(..., 'OptionName',optionValue, ...)

Input

• src Source image.
• center The transformation center; where the output precision is maximal.
• M Magnitude scale parameter. It determines the radius of the bounding circle to transform too

Output

• dst Destination image. It will have same size and type as src.

Options

• Interpolation Interpolation method, default 'Linear'. One of:
  • Nearest nearest neighbor interpolation
  • Linear bilinear interpolation
  • Cubic bicubic interpolation
  • Lanczos4 Lanczos interpolation over 8x8 neighborhood
• FillOutliers flag, fills all of the destination image pixels. If some of them correspond to outliers in the source image, they are set to zero. default true
• InverseMap flag, inverse transformation, default false. For example, polar transforms:
  • flag is not set: Forward transformation dst(rho,phi) = src(x,y)
  • flag is set: Inverse transformation dst(x,y) = src(rho,phi)

Transform the source image using the following transformation (See reference image in cv.linearPolar function):

dst(rho,phi) = src(x,y)
size(dst) <- size(src)

where:

I = (dx,dy) = (x-center(2), y-center(1))
rho = M * log(magnitude(I))
phi = Ky * angle(I)_{0..360 deg}

and:

M = size(src,2) / log(maxRadius)
Ky = size(src,1) / 360

The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking and so forth.

Note: To calculate magnitude and angle in degrees, cv.cartToPolar is used internally thus angles are measured from 0 to 360 with accuracy about 0.3 degrees.