Is there any way to the reduce pixel count in images without losing quality?

[anon2101]

So i just want to reduce the pixel count of an image from 16 megapixels to just under 2 megapixels. But there's a significant loss in quality of the image. Is there any way to not let this happen using gimp? Or if that's not possible via gimp, other free software or plugins that might help with this?

[PixLab]

just make a calculation 16 pixels to 2 pixels = thus you are losing 14 MP
Ok it's not really working this way, but... changing the size of an image will ALWAYS alter the quality of your pics, you do have software which MIGHT do a better job reducing an image (XnConvert comes to my mind) but do not expect miracle, at all, as you are *shrinking AND mixing pixels... (*pixels are "unshrinkable", but you got the point as you are reducing the number of pixels)

If you call quality the lack of sharpness ➤ the unsharp filter might help Filters ➤ Enhance ➤ Sharpen (unsharp mask)

but other all, shrinking from 16MP to 2MP ➤ you are loosing 8 times the number of data... squared! (not sure about the squared one, though, my math are so way out)
But you know what I mean

[rich2005]

By pixel count 16 Mp to 2 Mp throws away 85% of the pixels.
You can not keep the same level of detail and quality.

Edit:  I was a bit terse there, much depends on the image and the intended use.

This comparison in an image viewer and the downscaled image does not look too bad. https://i.imgur.com/UxNhYlS.jpg

Only when you zoom in does the loss of detail show, those stepped pixels. https://i.imgur.com/zin6tmb.jpg

In Gimp that looks worse. Image viewers / web browsers will 'improve' an image with a little blur. All in the eye of the beholder.

I pulled out a good ImageMagick down-scaling function

Code:

magick image.jpg -colorspace RGB -filter Lanczos -define filter:blur=.9891028367558475 -distort Resize 34% -colorspace sRGB downscaled.png

..and really no better than Gimp NoHalo algorithm.

[neurolurker]

Something to consider: The eyes of most beholders will have never seen what you have seen before you compressed the image. Most people - consumers, nonprofessionals - who see the compressed image can never make the comparison you are making and will simply accept what they see as what they are supposed to see.

[Ofnuts]

When you downscale, patterns that are close to the sale factor (for instance a 4px repeating pattern when you scale down by 4.05x) can produce aliasing. Such patterns will also include slightly slanted lines.

A counter-intuitive way to reduce aliasing is to blur the image before scaling down, to remove the high frequency components that will anyway not be visible in the final image.