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1

Even if you processed the raw files initially, when you upload them to sites such as google photos, they may compress them further to reduce the bandwidth needed to transmit them to viewers. This compression can also cause banding.


18

This is known as "banding". Dark parts in the picture have a small range of values (in a JPG, you only have 256 values per color), when you lighten them, you increase the gap between consecutive values as much as the values themselves. Since the gaps more or less follow a line they are very noticeable by our eyes. Several fixes are possible : If you have ...


5

This is named banding. And it's caused in your case by overprocessing the image. What you can do is to take the photo in RAW and postprocess it. When postprocessing mask the sky and do not increase the exposure there. At the end night sky is dark. You can also take two photos, one as it is and one for the buildings. And mix them keeping sky dark and ...


0

One good reason is a mindset of being literally "done" with the image the moment the shutter closes. The result is decided in that moment, and all that remains is deciding whether to discard, archive or publish it. .... There is often the statement that in the film era, people either postprocessed when printing from the negative, or had their lab do the ...


5

No need for post processing. Relative to the camera, the motorcycle and rider are not moving (unless the rider waves the selfie-stick) so they are sharp. The background (clouds and landscape) are changing very little due to the distance, so they also look sharp. The road and nearby shoulder to move quickly relative to the camera, so are subject to motion ...


3

Search eBay/Amazon etc for "Intervalometer" - prices around $£€ 10 - cheap as chips. They come with adaptors to fit just about any camera that can use one. Usually claim time-lapse intervals programmable up to 99 hours. They're all pretty generic Chinese devices, unbranded or branded with any number of different names. Bonus: even without batteries they ...


0

Your results are decidedly magenta and that is the opposite of where they should be. They should be green for an uncorrected bayer RGB. I suspect that your observed sigmoid correction was heavily influenced by the raw data already having a white balance correction applied in ACR. You may even be getting "doubled correction" at this point, but I don't know. ...


1

Observations: You are summing the values of each pixel, but your exposureAdjust() function assumes that after conditioning, each pixel will be in the range [0, 1). This is not correct. Assume a pixel's value in each of the 3 input images is, say, 50% full-scale (thus, 213 = 8192). Summing that three times yields 3 * 8192 = 24,576. Then the result after ...


2

More photos by Meridith Kohut may be found at Getty Images. Most of her images there look like this. It seems she keeps the exact formula to herself, but I see: Boosted shadows. Excessive sharpening. Under exposure (aka "expose to the right") Mismatched saturation. It seems you assume she uses HDR tonemapping techniques, but those usually have a different ...


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