Better image is it possible?

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I can not understand why there is a noise filter. All examples, which on the net are same and they are always adding noise firstly, after they filter to clean noise. Can ı improve a photo in terms of noise with Matlab.
And I have another question
I tried cameraman.tiff examples ı did but When ı try another example Myexample I failed
Error message was that
Error using medfilt2
Expected input number 1, A, to be two-dimensional.
Error in medfilt2>parse_inputs (line 106)
validateattributes(a, {'numeric','logical'}, {'2d','real'},
mfilename, 'A', 1);
Error in medfilt2 (line 48)
[a, mn, padopt] = parse_inputs(varargin{:});

Accepted Answer

Walter Roberson
Walter Roberson on 7 Dec 2018
Edited: Walter Roberson on 7 Dec 2018
the link is to a jpeg image . jpeg images are rarely grayscale: they are much much more likely to be rgb. grayscale jpeg are technically possible but in a couple of decades I have encountered only about two of them.
  2 Comments
Walter Roberson
Walter Roberson on 7 Dec 2018
Edited: Walter Roberson on 7 Dec 2018
The reason that people always start with a known image and add noise that they then remove, is that the processed image can then be compared to the original image in order to obtain a measurement of how well the noise removal went. Once you have developed a noise removal method and tested it on several known images and had success then you have some confidence that the technique will do well on additional images that you do not have the original for .
If I were to give you an image , perhaps an astronomical image, and ask you to denoise it, then what confidence would you have that you archieved a good result and that the messy blobs in the results were real measurements and not noise and not artifacts of over removing signals ? Remember that not all images have nice crisp boundaries, and that we do not know ahead of time what the "real" image is to visually compare to know when we have done the best job.
Answer: we can have confidence if we had previously tested the method on known data with similar structure , added noise of the same kind and magnitudes to the known image and did a good job of recovering .
Walter Roberson
Walter Roberson on 7 Dec 2018
Onur Üstüner comments:
includes important imformation

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