matlab用金字塔分解进行多尺度分解实现图像融合的代码

以下是使用拉普拉斯金字塔实现图像融合的MATLAB代码：

% 读入需要融合的图像
img1 = imread('image1.jpg');
img2 = imread('image2.jpg');

% 将图像转化为灰度图像
gray1 = rgb2gray(img1);
gray2 = rgb2gray(img2);

% 拉普拉斯金字塔分解
levels = 5; % 金字塔的层数
filterSize = 5; % 滤波器大小
gray1Pyr = laplacianPyramid(gray1, levels, filterSize);
gray2Pyr = laplacianPyramid(gray2, levels, filterSize);

% 图像融合
mergedPyr = cell(1, levels+1);
for i = 1:levels+1
    rows = size(gray1Pyr{i}, 1);
    cols = size(gray1Pyr{i}, 2);
    mergedPyr{i} = zeros(rows, cols);
    for r = 1:rows
        for c = 1:cols
            if abs(gray1Pyr{i}(r,c)) > abs(gray2Pyr{i}(r,c))
                mergedPyr{i}(r,c) = gray1Pyr{i}(r,c);
            else
                mergedPyr{i}(r,c) = gray2Pyr{i}(r,c);
            end
        end
    end
end

% 重建金字塔
mergedImg = reconstructLaplacianPyramid(mergedPyr, filterSize);

% 显示并保存融合图像
imshow(mergedImg);
imwrite(mergedImg, 'mergedImage.jpg');

% 拉普拉斯金字塔分解函数
function pyr = laplacianPyramid(img, levels, filterSize)
    pyr = cell(1, levels+1);
    pyr{1} = img;
    for i = 2:levels+1
        img = imfilter(img, fspecial('gaussian', filterSize, 0.5), 'symmetric', 'conv');
        img = img(1:2:end, 1:2:end);
        pyr{i} = imresize(imfilter(img, fspecial('gaussian', filterSize, 0.5), 'symmetric', 'conv'), size(pyr{i-1}), 'bilinear');
        pyr{i-1} = pyr{i-1} - pyr{i};
    end
end

% 重建拉普拉斯金字塔函数
function img = reconstructLaplacianPyramid(pyr, filterSize)
    levels = length(pyr) - 1;
    img = pyr{levels+1};
    for i = levels:-1:1
        img = imresize(img, size(pyr{i}), 'bilinear');
        img = img + pyr{i};
    end
end

这段代码中，首先读入需要融合的两张图像，将其转化为灰度图像。然后使用laplacianPyramid函数对两张灰度图像进行拉普拉斯金字塔分解，得到两个金字塔。接着对不同分辨率的图像进行融合，得到最终的融合金字塔。最后使用reconstructLaplacianPyramid函数重建金字塔，得到最终的融合图像，并将其保存到本地。