I have been told that this photograph contains noise and is muddy. It is difficult for me to identify noise in a photograph until it is in extremes.
Are there any softwares available which detect the noisy areas in a photograph?
Photography Stack Exchange is a question and answer site for professional, enthusiast and amateur photographers. It only takes a minute to sign up.Sign up to join this community
I'm not aware of any software whose purpose is to simply alert you to noise. There are noise removal tools to remove noise though, and thatsoftware will show before and after the noise reduction.
Your image doesn't immediately strike me as noisy. However it's a dark image, and shadows is where you usually find noise.
To see the noise, it's best to zoom in to 100-200%, since noise is at the pixel level and you want a lot of magnification to see individual pixels.
Below is a small bit of your original image. You can see that the transition from light to dark isn't really smooth. You can see spots. I think they look "blocky" which means they may be more due to JPG compression rather than sensor noise. It's hard to see, but these spots are not just a pixel or two, but blocks of pixels as far as I can tell.
Applying a small amount of noise reduction to the image gives the following result, which is a lot smoother. It's removed the spots, whether they were JPG artifacts or actual noise. Whether you can tell the difference looking at the full image at normal resolution is debatable. If you can't easily see the noise, and have to magnify to 200% to find it, in my opinion it doesn't really matter.
It's not automatic, but one way to try to identify noise yourself is to adjust the contrast. For this photo, I used the Curves tool to bring out the banding I saw from certain angles on my laptop's screen when looking at the JPG posted in the question:
Having different levels of noise across the image makes the noise more obvious (to me, at least) than a consistent level of noise across the image (which I can tune out). (In this case, with a couple fairly-well-defined noise boundaries roughly in the middle of the image, those boundaries contribute to making the image feel like it's composed of two separate pictures.)
This view of the picture also highlights the lens flare on the left half of the image (another reason, perhaps, why this picture was perceived as two separate images: there is flare in one half, but not the other).