# Data loss in image

3 views (last 30 days)
dani elias on 15 Oct 2022
Commented: dani elias on 16 Oct 2022
I have an encrypted image,I wantit to like these so I can be able to test for data loss
Jan on 16 Oct 2022
Remember that insertShape replies an RGB image.

Image Analyst on 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 on 16 Oct 2022
Thank you, this works perfect.

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