How to sharpen and get details of the image2 like original one

I was working on a research, I was having a noisy image and a clean image,

I proccessed a noisy image with two algo getting pimg1 and pimg2, I was confused how to make any one of it more like this clean image

I tried fft, imsharpen but nothing it look good

Clean image: image1

I processed the noisy image and got my image: pimg1

pimg2

[Benjamin Thompson]

If this is the topic of your research then please post the answer when you complete your research. If you have a specific question about Mathworks software then please ask.

Answer 1

[yanqi liu]

yes，sir，may be change the background color，and make the coin to white，such as

clc; clear all; close all;
im = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/895635/image.png');
im = imresize(im,0.2,'bilinear');
im2 = rgb2gray(im);
bw = imbinarize(im2,'adaptive','ForegroundPolarity','dark','Sensitivity',0.45);
mk = bwareafilt(bw,1);
bw2 = imclearborder(bw);
bw2 = imfill(bw2, 'holes');
bw2 = bwareafilt(bw2,1);
bw2 = logical(bw2.*bw);
figure; imshow(bw2);

im3 = imadd(im2uint8(im2), im2uint8(bw2));
figure; imshow(im3);

Answer 2

[Image Analyst]

"I was confused how to make any one of it more like this " <== Not sure I understand. Do you not know how to create a function that you can pass in different images to, and have it process them in the same way? If not, it probably goes over it in this:

MATLAB Academy - Free 2 hour training

[shubham kumar gupta]

Thank you for you comment,

My algo works on too much or very noisy img (0.1% close to clean img) but after the processing I got these two images(90% close to clean img), Now i was struggling to make it little bit better after that,

😅I know how to make functions, I was trying to apply other filters over this images to make it little bit better just

[Image Analyst]

Well I don't know what you're after. There are tons of filters to produce an infinite number of appearances. In addition, there are many, many denoising methods.

Try this link:

Modern tour of image filtering denoising