Don’t know what is wrong with my output of this code
function [MOVINGREG] = registerMarsImages(MOVING,FIXED)
% Convert images to grayscale if they are RGB
if size(MOVING, 3) == 3
MOVING = rgb2gray(MOVING);
end
if size(FIXED, 3) == 3
FIXED = rgb2gray(FIXED);
end
% Detect features in both images
points1 = detectSURFFeatures(MOVING, ‘MetricThreshold’, 1000);
points2 = detectSURFFeatures(FIXED, ‘MetricThreshold’, 1000);
% Extract features from both images
[features1, valid_points1] = extractFeatures(MOVING, points1);
[features2, valid_points2] = extractFeatures(FIXED, points2);
% Match features by using their descriptors
indexPairs = matchFeatures(features1, features2, ‘MatchThreshold’, 10, ‘MaxRatio’, 0.7);
% Retrieve locations of corresponding points for each image
matchedPoints1 = valid_points1(indexPairs(:, 1), :);
matchedPoints2 = valid_points2(indexPairs(:, 2), :);
% Estimate the transformation between the moving and fixed images
[tform, inlierIdx] = estimateGeometricTransform2D(matchedPoints1, matchedPoints2, ‘projective’, ‘Confidence’, 99.9, ‘MaxNumTrials’, 2000);
% Get the output limits for the transformation
[xLimitsMoving, yLimitsMoving] = outputLimits(tform, [1 size(MOVING, 2)], [1 size(MOVING, 1)]);
[xLimitsFixed, yLimitsFixed] = outputLimits(projective2d(eye(3)), [1 size(FIXED, 2)], [1 size(FIXED, 1)]);
% Determine the size of the panorama
xMin = min([xLimitsMoving xLimitsFixed]);
xMax = max([xLimitsMoving xLimitsFixed]);
yMin = min([yLimitsMoving yLimitsFixed]);
yMax = max([yLimitsMoving yLimitsFixed]);
width = round(xMax – xMin);
height = round(yMax – yMin);
% Create an empty panorama canvas
panorama = zeros(height, width, ‘like’, FIXED);
% Create reference objects for the panorama and the fixed image
panoramaView = imref2d([height width], [xMin xMax], [yMin yMax]);
fixedRef = imref2d(size(FIXED), [xLimitsFixed(1) xLimitsFixed(2)], [yLimitsFixed(1) yLimitsFixed(2)]);
% Warp the moving image into the panorama
registered = imwarp(MOVING, tform, ‘OutputView’, panoramaView);
% Overlay the fixed image onto the panorama
panorama = imwarp(FIXED, projective2d(eye(3)), ‘OutputView’, panoramaView, ‘FillValues’, 0);
panorama = max(panorama, registered);
% Resize the panorama to fit within 1024×1024
scaleFactor = min(1024 / width, 1024 / height);
panoramaScaled = imresize(panorama, scaleFactor);
% Create a 1024×1024 canvas
finalPanorama = zeros(1024, 1024, ‘like’, FIXED);
% Determine the position to center the scaled stitched image within the canvas
[scaledHeight, scaledWidth] = size(panoramaScaled);
xOffset = max(0, round((1024 – scaledWidth) / 2));
yOffset = max(0, round((1024 – scaledHeight) / 2));
% Place the scaled stitched image onto the 1024×1024 canvas
finalPanorama(yOffset + (1:scaledHeight), xOffset + (1:scaledWidth)) = panoramaScaled;
% Store the registered image
MOVINGREG.RegisteredImage = finalPanorama;
% Store the transformation object
MOVINGREG.Transformation = tform;
end
% Load the images
fixedImg = imread("sol_03333_opgs_edr_ncam_NLB_693387385EDR_F0921230NCAM00259M_.JPG");
leftImg = imread("sol_03333_opgs_edr_ncam_NLB_693387301EDR_F0921230NCAM00259M_.JPG");
% Register the two images
reg = registerMarsImages(leftImg, fixedImg)
figure; imshow(reg.RegisteredImage)function [MOVINGREG] = registerMarsImages(MOVING,FIXED)
% Convert images to grayscale if they are RGB
if size(MOVING, 3) == 3
MOVING = rgb2gray(MOVING);
end
if size(FIXED, 3) == 3
FIXED = rgb2gray(FIXED);
end
% Detect features in both images
points1 = detectSURFFeatures(MOVING, ‘MetricThreshold’, 1000);
points2 = detectSURFFeatures(FIXED, ‘MetricThreshold’, 1000);
% Extract features from both images
[features1, valid_points1] = extractFeatures(MOVING, points1);
[features2, valid_points2] = extractFeatures(FIXED, points2);
% Match features by using their descriptors
indexPairs = matchFeatures(features1, features2, ‘MatchThreshold’, 10, ‘MaxRatio’, 0.7);
% Retrieve locations of corresponding points for each image
matchedPoints1 = valid_points1(indexPairs(:, 1), :);
matchedPoints2 = valid_points2(indexPairs(:, 2), :);
% Estimate the transformation between the moving and fixed images
[tform, inlierIdx] = estimateGeometricTransform2D(matchedPoints1, matchedPoints2, ‘projective’, ‘Confidence’, 99.9, ‘MaxNumTrials’, 2000);
% Get the output limits for the transformation
[xLimitsMoving, yLimitsMoving] = outputLimits(tform, [1 size(MOVING, 2)], [1 size(MOVING, 1)]);
[xLimitsFixed, yLimitsFixed] = outputLimits(projective2d(eye(3)), [1 size(FIXED, 2)], [1 size(FIXED, 1)]);
% Determine the size of the panorama
xMin = min([xLimitsMoving xLimitsFixed]);
xMax = max([xLimitsMoving xLimitsFixed]);
yMin = min([yLimitsMoving yLimitsFixed]);
yMax = max([yLimitsMoving yLimitsFixed]);
width = round(xMax – xMin);
height = round(yMax – yMin);
% Create an empty panorama canvas
panorama = zeros(height, width, ‘like’, FIXED);
% Create reference objects for the panorama and the fixed image
panoramaView = imref2d([height width], [xMin xMax], [yMin yMax]);
fixedRef = imref2d(size(FIXED), [xLimitsFixed(1) xLimitsFixed(2)], [yLimitsFixed(1) yLimitsFixed(2)]);
% Warp the moving image into the panorama
registered = imwarp(MOVING, tform, ‘OutputView’, panoramaView);
% Overlay the fixed image onto the panorama
panorama = imwarp(FIXED, projective2d(eye(3)), ‘OutputView’, panoramaView, ‘FillValues’, 0);
panorama = max(panorama, registered);
% Resize the panorama to fit within 1024×1024
scaleFactor = min(1024 / width, 1024 / height);
panoramaScaled = imresize(panorama, scaleFactor);
% Create a 1024×1024 canvas
finalPanorama = zeros(1024, 1024, ‘like’, FIXED);
% Determine the position to center the scaled stitched image within the canvas
[scaledHeight, scaledWidth] = size(panoramaScaled);
xOffset = max(0, round((1024 – scaledWidth) / 2));
yOffset = max(0, round((1024 – scaledHeight) / 2));
% Place the scaled stitched image onto the 1024×1024 canvas
finalPanorama(yOffset + (1:scaledHeight), xOffset + (1:scaledWidth)) = panoramaScaled;
% Store the registered image
MOVINGREG.RegisteredImage = finalPanorama;
% Store the transformation object
MOVINGREG.Transformation = tform;
end
% Load the images
fixedImg = imread("sol_03333_opgs_edr_ncam_NLB_693387385EDR_F0921230NCAM00259M_.JPG");
leftImg = imread("sol_03333_opgs_edr_ncam_NLB_693387301EDR_F0921230NCAM00259M_.JPG");
% Register the two images
reg = registerMarsImages(leftImg, fixedImg)
figure; imshow(reg.RegisteredImage) function [MOVINGREG] = registerMarsImages(MOVING,FIXED)
% Convert images to grayscale if they are RGB
if size(MOVING, 3) == 3
MOVING = rgb2gray(MOVING);
end
if size(FIXED, 3) == 3
FIXED = rgb2gray(FIXED);
end
% Detect features in both images
points1 = detectSURFFeatures(MOVING, ‘MetricThreshold’, 1000);
points2 = detectSURFFeatures(FIXED, ‘MetricThreshold’, 1000);
% Extract features from both images
[features1, valid_points1] = extractFeatures(MOVING, points1);
[features2, valid_points2] = extractFeatures(FIXED, points2);
% Match features by using their descriptors
indexPairs = matchFeatures(features1, features2, ‘MatchThreshold’, 10, ‘MaxRatio’, 0.7);
% Retrieve locations of corresponding points for each image
matchedPoints1 = valid_points1(indexPairs(:, 1), :);
matchedPoints2 = valid_points2(indexPairs(:, 2), :);
% Estimate the transformation between the moving and fixed images
[tform, inlierIdx] = estimateGeometricTransform2D(matchedPoints1, matchedPoints2, ‘projective’, ‘Confidence’, 99.9, ‘MaxNumTrials’, 2000);
% Get the output limits for the transformation
[xLimitsMoving, yLimitsMoving] = outputLimits(tform, [1 size(MOVING, 2)], [1 size(MOVING, 1)]);
[xLimitsFixed, yLimitsFixed] = outputLimits(projective2d(eye(3)), [1 size(FIXED, 2)], [1 size(FIXED, 1)]);
% Determine the size of the panorama
xMin = min([xLimitsMoving xLimitsFixed]);
xMax = max([xLimitsMoving xLimitsFixed]);
yMin = min([yLimitsMoving yLimitsFixed]);
yMax = max([yLimitsMoving yLimitsFixed]);
width = round(xMax – xMin);
height = round(yMax – yMin);
% Create an empty panorama canvas
panorama = zeros(height, width, ‘like’, FIXED);
% Create reference objects for the panorama and the fixed image
panoramaView = imref2d([height width], [xMin xMax], [yMin yMax]);
fixedRef = imref2d(size(FIXED), [xLimitsFixed(1) xLimitsFixed(2)], [yLimitsFixed(1) yLimitsFixed(2)]);
% Warp the moving image into the panorama
registered = imwarp(MOVING, tform, ‘OutputView’, panoramaView);
% Overlay the fixed image onto the panorama
panorama = imwarp(FIXED, projective2d(eye(3)), ‘OutputView’, panoramaView, ‘FillValues’, 0);
panorama = max(panorama, registered);
% Resize the panorama to fit within 1024×1024
scaleFactor = min(1024 / width, 1024 / height);
panoramaScaled = imresize(panorama, scaleFactor);
% Create a 1024×1024 canvas
finalPanorama = zeros(1024, 1024, ‘like’, FIXED);
% Determine the position to center the scaled stitched image within the canvas
[scaledHeight, scaledWidth] = size(panoramaScaled);
xOffset = max(0, round((1024 – scaledWidth) / 2));
yOffset = max(0, round((1024 – scaledHeight) / 2));
% Place the scaled stitched image onto the 1024×1024 canvas
finalPanorama(yOffset + (1:scaledHeight), xOffset + (1:scaledWidth)) = panoramaScaled;
% Store the registered image
MOVINGREG.RegisteredImage = finalPanorama;
% Store the transformation object
MOVINGREG.Transformation = tform;
end
% Load the images
fixedImg = imread("sol_03333_opgs_edr_ncam_NLB_693387385EDR_F0921230NCAM00259M_.JPG");
leftImg = imread("sol_03333_opgs_edr_ncam_NLB_693387301EDR_F0921230NCAM00259M_.JPG");
% Register the two images
reg = registerMarsImages(leftImg, fixedImg)
figure; imshow(reg.RegisteredImage) matlab code, matlab, output, image stitching, panorama MATLAB Answers — New Questions