Proposed-Code/fuseImage.m at main · arbabsufyan/Proposed-Code · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
function [ F ] = fuseImage(I,scale)


addpath('Pyramid_Decomposition');
addpath('Guided_Filter');
addpath('Dense_SIFT');

tic
%%
[H, W, C, N]=size(I);
imgs=im2double(I);
IA=zeros(H,W,C,N);
for i=1:N
IA(:,:,:,i)=enhnc(imgs(:,:,:,i));

end
%%
imgs_gray=zeros(H,W,N);
for i=1:N
    imgs_gray(:,:,i)=rgb2gray(IA(:,:,:,i));
end
%
% %dense sift calculation
dsifts=zeros(H,W,32,N, 'single');
for i=1:N
    img=imgs_gray(:,:,i);
    ext_img=img_extend(img,scale/2-1);
    [dsifts(:,:,:,i)] = DenseSIFT(ext_img, scale, 1);

end
%%
%local contrast
contrast_map=zeros(H,W,N);
for i=1:N
    contrast_map(:,:,i)=sum(dsifts(:,:,:,i),3);

end


%winner-take-all weighted average strategy for local contrast

[x, labels]=max(contrast_map,[],3);
clear x;
for i=1:N
    mono=zeros(H,W);
    mono(labels==i)=1;
    contrast_map(:,:,i)=mono;

end


%% Structure
h = [1 -1];
structure_map=zeros(H,W,N);

for i=1:N
structure_map(:,:,i) = abs(conv2(imgs_gray(:,:,i),h,'same')) + abs(conv2(imgs_gray(:,:,i),h','same')); %EQ 13


end


%winner-take-all weighted average strategy for structure

[a, label]=max(structure_map,[],3);
clear x;
for i=1:N
    monoo=zeros(H,W);
    monoo(label==i)=1;
    structure_map(:,:,i)=monoo;

end

%%
weight_map=structure_map.*contrast_map;


%weight map refinement using Guided Filter
for i=1:N

    weight_map(:,:,i) = fastGF(weight_map(:,:,i),12,0.25,2.5);

end


% normalizing weight maps
%
weight_map = weight_map + 10^-25; %avoids division by zero
weight_map = weight_map./repmat(sum(weight_map,3),[1 1 N]);

%% Pyramid Decomposition

% create empty pyramid
pyr = gaussian_pyramid(zeros(H,W,3));
nlev = length(pyr);

% multiresolution blending
for i = 1:N
    % construct pyramid from each input image
    pyrW = gaussian_pyramid(weight_map(:,:,i));

    pyrI = laplacian_pyramid(imgs(:,:,:,i));

    % blend
    for b = 1:nlev
        w = repmat(pyrW{b},[1 1 3]);

        pyr{b} = pyr{b} + w .*pyrI{b};
    end

end

% reconstruct
F = reconstruct_laplacian_pyramid(pyr);

toc

end