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 1024x1024
    scaleFactor = min(1024 / width, 1024 / height);
    panoramaScaled = imresize(panorama, scaleFactor);

    % Create a 1024x1024 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 1024x1024 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)

[Steven Lord]

What did you expect this code to return? That picture looks reasonable to me.

[Asuka]

This is the final assignment from MATLAB course offered by MathWork on Coursera, and the auto grading system gave a feedback as below.

[Asuka]

And here's the requirement for Reistration part:

Register the Images

Use the Registration Estimator app to create a function that registers the images. Then, use that function to return the registration structure.

When you're happy with your registration function, return to the course and use the online grader to check if it gives the correct result.

Answer 1

[Cris LaPierre]

Your result has stitched all 3 images together. However, the function should be returning a single image (the moving one only).

"The grader is checking that your registration function can produce a result close to the expected solution registration function. You will still need to correctly warp and stitch the images together."

Make sure you are submitting code generated by the Registration Estimator app.