Point sampled:
Simplest method. When downsizing an image, it simply picks a single pixel value from the original image to represent that area in the smaller image.
For noise reduction: Not very effective. Noise is random. Picking a single pixel value might capture a noisy pixel, not necessarily an average representation of the area.
Averaged Down:
More effective for noise reduction. When downsizing, it calculates the average color value of a group of pixels from the original image. This group corresponds to the area represented by a single pixel in the smaller image. By averaging, the random noise gets somewhat smoothed out.
aidangarde
It makes sense that the averaged-down image appears more smooth, but it must lose detail by averaging out pixel-wide partners. Is there a quantifiable way to measure the noise of the picture and determine whether averaged down or point sampled is the preferable method?
cvankeuren
Are there specific cases where point sampling yields a better image than averaged down? Imaging a world where cost/speed doesn't matter of course, I'm curious if averaged down always performs better.
TiaJain
To answer cvankeuren's question, I believe that point sampling might yield a better image than averaging down in cases where preserving sharp edges and fine detail is more important than reducing noise (so more useful in line art/images w/ distinct, high-contrast boundaries) where avging could result in unwanted blurring.
Zzz212zzZ
Taking more pixels into consideration (just as what averaged down does) is fairly a good strategy because it tends to store more information, instead, the point sampled strategy just throws these pixels away. By the way, the averaged pixel is more smooth.
Conclusion:
Point sampled: Simplest method. When downsizing an image, it simply picks a single pixel value from the original image to represent that area in the smaller image. For noise reduction: Not very effective. Noise is random. Picking a single pixel value might capture a noisy pixel, not necessarily an average representation of the area.
Averaged Down: More effective for noise reduction. When downsizing, it calculates the average color value of a group of pixels from the original image. This group corresponds to the area represented by a single pixel in the smaller image. By averaging, the random noise gets somewhat smoothed out.
It makes sense that the averaged-down image appears more smooth, but it must lose detail by averaging out pixel-wide partners. Is there a quantifiable way to measure the noise of the picture and determine whether averaged down or point sampled is the preferable method?
Are there specific cases where point sampling yields a better image than averaged down? Imaging a world where cost/speed doesn't matter of course, I'm curious if averaged down always performs better.
To answer cvankeuren's question, I believe that point sampling might yield a better image than averaging down in cases where preserving sharp edges and fine detail is more important than reducing noise (so more useful in line art/images w/ distinct, high-contrast boundaries) where avging could result in unwanted blurring.
Taking more pixels into consideration (just as what averaged down does) is fairly a good strategy because it tends to store more information, instead, the point sampled strategy just throws these pixels away. By the way, the averaged pixel is more smooth.