Resizes an image

dst = cv.resize(src, dsize)
dst = cv.resize(src, fx, fy)
dst = cv.resize(..., 'OptionName',optionValue, ...)

Input

• src input image.
• dsize output image size [w,h].
• fx Scale factors along the horizontal axis.
• fy Scale factors along the vertical axis.

When scale factors are specified, the output image size is computed as: dsize = round([fx*size(src,2), fy*size(src,1)]).

Output

• dst output image. It has the size dsize or the size computed from size(src) and fx and fy. The type of dst is the same as of src.

Options

• Interpolation interpolation method, default 'Linear'. One of:
  • Nearest a nearest-neighbor interpolation
  • Linear a bilinear interpolation (used by default)
  • Cubic a bicubic interpolation over 4x4 pixel neighborhood
  • Area resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire-free results. But when the image is zoomed, it is similar to the 'Nearest' method.
  • Lanczos4 a Lanczos interpolation over 8x8 pixel neighborhood
  • LinearExact a bit exact bilinear interpolation

The function cv.resize resizes the image src down to or up to the specified size. The size and type of dst are derived from src, dsize, fx and fy. If you want to resize src so that it fits a specified size, you may call the function as follows:

dst = cv.resize(src, [w,h], 'Interpolation',interp)

If you want to decimate the image by factor of 2 in each direction, you can call the function this way:

dst = cv.resize(src, 0.5, 0.5, 'Interpolation',interp)

To shrink an image, it will generally look best with 'Area' interpolation, whereas to enlarge an image, it will generally look best with 'Cubic' (slow) or 'Linear' (faster but still looks OK).