# Data loss in image

4 vues (au cours des 30 derniers jours)
dani elias le 15 Oct 2022
Commenté : dani elias le 16 Oct 2022
I have an encrypted image,I wantit to like these so I can be able to test for data loss
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dani elias le 15 Oct 2022
Thank you
Jan le 16 Oct 2022
Remember that insertShape replies an RGB image.

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### Réponse acceptée

Image Analyst le 16 Oct 2022
Try this on your recovered image
% Create "recovered" image.
grayImage = imnoise(grayImage, "gaussian", 0, .01);
[rows, columns, numberOfColorChannels] = size(grayImage)
rows = 256
columns = 256
numberOfColorChannels = 1
subplot(2, 1, 1);
imshow(grayImage, []);
title('Initial Image')
% Define fraction of pixels to blacken in the middle.
pct = 0.25;
% Determine how many pixels that is.
numBlackPixels = pct * numel(grayImage)
numBlackPixels = 16384
% Assume it's a square and determine the width of the square
squareWidth = sqrt(numBlackPixels)
squareWidth = 128
% Get the rows of the square in the original image
row1 = round(rows/2 - squareWidth/2)
row1 = 64
row2 = round(rows/2 + squareWidth/2)
row2 = 192
% Get the columns of the square in the original image
col1 = round(columns/2 - squareWidth/2)
col1 = 64
col2 = round(columns/2 + squareWidth/2)
col2 = 192
% Do the blackening:
grayImage2 = grayImage; % Initialize
grayImage2(row1:row2, col1:col2) = 0; % Blacken square in the middle
subplot(2, 1, 2);
imshow(grayImage2, [])
title('Output Image')
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dani elias le 16 Oct 2022
Thank you, this works perfect.

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