Resize image, compute, resize back to original

asked 2014-09-08 04:29:47 -0600

razvan
46 ●2 ●6 ●9 http://www.mobileway.net/

updated 2014-09-08 04:31:29 -0600

Hello,

This might seem like a simple issue but here is what I need help with:

for example I receive a 1280960 image, I then resize it to 640480 or 320*240 pixels
I do some processing and I end up with 2 points: P1 at (x1,y1) and P2 at (x2,y2)
how do I draw these points on the original input image with the corresponding location?

I got to resize the image and computed the 2 points describing a line. I am stuck in the last part, resizing & displaying the 2 points back to the original image.

I am using Android for development. Regards!

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May be you can use the scale factor for x & y (used for reducing size) to map the point P1 in original image.

jamesnzt ( 2014-09-08 04:59:16 -0600 )edit

1

Scale factor didn't work as expected, maybe it's an error from my algorithm but if I reduce the image to half ( /2 ) then to map the points back they should be multiplied by 2 ( x1 *= 2, y1 *= 2, etc.) but they show in wrong places..

razvan ( 2014-09-08 11:08:51 -0600 )edit

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answered 2014-09-08 06:24:40 -0600

Balaji R

2065 ●4 ●22 ●45 https://in.linkedin.co...

Consider a trivial example: the image size is reduced exactly by half.

So, the cartesian coordinate (x, y) in the original image becomes coordinate (x/2, y/2) in the reduced image, and coordinate (x', y') in the reduced image corresponds to coordinate (x2, y2) in the original image.

Of course, fractional coordinates get typically rounded off, in a reduced scale image, so the exact mapping is only possible for even-numbered coordinates in this example's original image.

Generalizing this, if the image's width is scaled by a factor of w horizontally and h vertically, coordinate (x, y) becomes coordinate(xw, yh), rounded off. In the example I gave, both w and h are 1/2, or .5

You should be able to figure out the values of w and h yourself, and be able to map the coordinates trivially. Of course, due to rounding off, you will not be able to compute the exact coordinates in the original image.

Ref: Thanks for the answer from this thread.

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answered 2019-04-26 17:51:03 -0600

hanifalisohag
11 ●1

There are some interpolation algorithms in OpenCV and You can find all the examples here: How to resize images in OpenCV python

Code:

image_scaled=cv2.resize(image,None,fx=.75,fy=.75,interpolation = cv2.INTER_LINEAR)
img_double=cv2.resize(image,None,fx=2,fy=2,interpolation=cv2.INTER_CUBIC)
image_resize=cv2.resize(image,(200,300),interpolation=cv2.INTER_AREA)
image_resize=cv2.resize(image,(500,400),interpolation=cv2.INTER_LANCZOS4)

INTER_NEAREST – a nearest-neighbor interpolation
INTER_LINEAR – a bilinear interpolation (used by default)
INTER_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 INTER_NEAREST method. I
NTER_CUBIC – a bicubic interpolation over 4×4 pixel
neighborhood
INTER_LANCZOS4 – a Lanczos interpolation over 8×8 pixel
neighborhood

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Resize image, compute, resize back to original

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