matlab图像处理空间滤波和频域滤波代码

由于空间滤波和频域滤波的具体实现方式和算法多种多样，因此无法提供一份通用的代码。以下是一些常见的图像处理滤波算法的 MATLAB 代码示例：

1. 均值滤波

空间滤波：

function output = meanFilter(input, maskSize)
    [m, n] = size(input);
    output = zeros(m, n);
    mask = ones(maskSize) / maskSize^2;
    padSize = floor(maskSize / 2);
    padded = padarray(input, [padSize padSize], 'replicate');
    for i = 1:m
        for j = 1:n
            window = padded(i:i+maskSize-1, j:j+maskSize-1);
            output(i, j) = sum(sum(window .* mask));
        end
    end
end

频域滤波：

function output = meanFilterFreq(input, maskSize)
    [m, n] = size(input);
    output = zeros(m, n);
    mask = ones(maskSize) / maskSize^2;
    padSize = floor(maskSize / 2);
    padded = padarray(input, [padSize padSize], 'replicate');
    paddedFreq = fft2(padded);
    maskFreq = fft2(mask, m+padSize*2, n+padSize*2);
    outputFreq = paddedFreq .* maskFreq;
    output = real(ifft2(outputFreq));
    output = output(padSize+1:end-padSize, padSize+1:end-padSize);
end

2. 中值滤波

空间滤波：

function output = medianFilter(input, maskSize)
    [m, n] = size(input);
    output = zeros(m, n);
    padSize = floor(maskSize / 2);
    padded = padarray(input, [padSize padSize], 'replicate');
    for i = 1:m
        for j = 1:n
            window = padded(i:i+maskSize-1, j:j+maskSize-1);
            output(i, j) = median(window(:));
        end
    end
end

3. 高斯滤波

空间滤波：

function output = gaussianFilter(input, sigma)
    [m, n] = size(input);
    output = zeros(m, n);
    maskSize = ceil(sigma * 6);
    if mod(maskSize, 2) == 0
        maskSize = maskSize + 1;
    end
    padSize = floor(maskSize / 2);
    mask = fspecial('gaussian', maskSize, sigma);
    padded = padarray(input, [padSize padSize], 'replicate');
    for i = 1:m
        for j = 1:n
            window = padded(i:i+maskSize-1, j:j+maskSize-1);
            output(i, j) = sum(sum(window .* mask));
        end
    end
end

频域滤波：

function output = gaussianFilterFreq(input, sigma)
    [m, n] = size(input);
    output = zeros(m, n);
    maskSize = ceil(sigma * 6);
    if mod(maskSize, 2) == 0
        maskSize = maskSize + 1;
    end
    padSize = floor(maskSize / 2);
    mask = fspecial('gaussian', maskSize, sigma);
    padded = padarray(input, [padSize padSize], 'replicate');
    paddedFreq = fft2(padded);
    maskFreq = fft2(mask, m+padSize*2, n+padSize*2);
    outputFreq = paddedFreq .* maskFreq;
    output = real(ifft2(outputFreq));
    output = output(padSize+1:end-padSize, padSize+1:end-padSize);
end