領域展開

1
function choose_image(app)
2
    file = uigetfile("", "选择输入图像")
3
    if isempty(file)
4
        return
5
    end
6

7
    app.InputFilePicker.Value = file
8
    app.InputImage.ImageSource = file
9
    app.OutputImage.ImageSource = raw""
10
    app.StatusLabel.Text = "已加载图像：" * file
11
end

1
function InputImageClickedFcn(app, event)
2
    app.choose_image()
3
end
4

5
function SelectImageButtonPushed(app, event)
6
    app.choose_image()
7
end

1
function center_crop_square(app, img)
2
    dims = size(img)
3
    height = dims[1]
4
    width = dims[2]
5
    side = min(height, width)
6

7
    row_start = Int(floor((height - side) / 2)) + 1
8
    col_start = Int(floor((width - side) / 2)) + 1
9
    rows = row_start:(row_start + side - 1)
10
    cols = col_start:(col_start + side - 1)
11

12
    if length(dims) >= 3
13
        return img[rows, cols, :]
14
    end
15

16
    return img[rows, cols]
17
end

1
function image_to_gray_float(app, img)
2
    pixel_type = eltype(img)
3

4
    if length(size(img)) >= 3 && size(img, 3) >= 3
5
        r = float.(img[:, :, 1])
6
        g = float.(img[:, :, 2])
7
        b = float.(img[:, :, 3])
8
        gray = 0.2989 .* r .+ 0.5870 .* g .+ 0.1140 .* b
9
    else
10
        gray = float.(img)
11
    end
12

13
    if pixel_type <: Unsigned
14
        return gray ./ float(typemax(pixel_type))
15
    end
16

17
    max_value = maximum(gray)
18
    if max_value > 1
19
        return gray ./ 255.0
20
    end
21

22
    return gray
23
end

1
function compress_with_eigen(app, gray, ratio)
2
    matrix = Matrix{Float64}(gray)
3
    n = size(matrix, 1)
4
    keep_count = max(1, min(n, Int(ceil(ratio * n))))
5

6
    factors = eigen(matrix)
7
    values = factors.values
8
    vectors = factors.vectors
9
    order = sortperm(abs.(values), rev=true)
10
    kept = order[1:keep_count]
11

12
    compressed_values = zeros(eltype(values), length(values))
13
    compressed_values[kept] = values[kept]
14

15
    reconstructed = vectors * diagm(compressed_values) / vectors
16
    reconstructed = real.(reconstructed)
17

18
    return map(value -> app.clamp01(value), reconstructed), keep_count, n
19
end

1
function clamp01(app, value)
2
    if isnan(value)
3
        return 0.0
4
    elseif value < 0
5
        return 0.0
6
    elseif value > 1
7
        return 1.0
8
    end
9

10
    return value
11
end

1
function process_image(app)
2
    source_path = app.InputFilePicker.Value
3
    if isempty(source_path) || !isfile(source_path)
4
        errordlg("请先选择一幅输入图像。", "缺少输入")
5
        return
6
    end
7

8
    ratio = app.RetainRatioEditField.Value
9
    if ratio <= 0 || ratio > 1
10
        errordlg("保留特征值比重必须位于 (0, 1]。", "参数错误")
11
        return
12
    end
13

14
    img = imread(source_path)
15
    if img isa Tuple
16
        img = img[1]
17
    end
18

19
    cropped = app.center_crop_square(img)
20
    gray = app.image_to_gray_float(cropped)
21
    reconstructed, keep_count, matrix_size =
22
        app.compress_with_eigen(gray, ratio)
23

24
    crop_path = joinpath(tempdir(), "syslab_evd_input_square.png")
25
    output_path = joinpath(tempdir(), "syslab_evd_reconstruction.png")
26
    imwrite(cropped, crop_path)
27
    imwrite(reconstructed, output_path)
28

29
    app.InputImage.ImageSource = crop_path
30
    app.OutputImage.ImageSource = output_path
31
    app.StatusLabel.Text =
32
        "完成：裁剪为 $(matrix_size)x$(matrix_size)，保留 $(keep_count)/$(matrix_size) 个特征值。"
33
end

1
code = read(joinpath(@__DIR__, "app.jl"), String)
2
Meta.parseall(code)
3

4
img = reshape(range(0, 1, length=64), 8, 8)
5
reconstructed, keep_count, matrix_size = compress_with_eigen(img, 0.25)
6

7
@assert size(reconstructed) == (8, 8)
8
@assert keep_count == 2
9
@assert matrix_size == 8
10
@assert minimum(reconstructed) >= 0
11
@assert maximum(reconstructed) <= 1

1
app.jl parse ok
2
core eigen compression ok
3
image write ok