显著性检测(saliency detection)评价指标之KL散度距离Matlab代码实现

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步骤1：先定义KLdiv函数：

function score = KLdiv(saliencyMap, fixationMap)

% saliencyMap is the saliency map

% fixationMap is the human fixation map

map1 = im2double(imresize(saliencyMap, size(fixationMap)));

map2 = im2double(fixationMap);

% make sure map1 and map2 sum to 1

if any(map1(:))

    map1 = map1/sum(map1(:));

end

if any(map2(:))

    map2 = map2/sum(map2(:));

end

% compute KL-divergence

score = sum(sum(map2 .* log(eps + map2./(map1+eps))));

步骤2：再写一个主函数调用它：

clear;

clc;

smap_path='E:\Dataset180303\final_data\smap_Result1\';

gmap_path='E:\Dataset180303\final_data\image_resize_gt\';

smap_file=dir(smap_path);

for j=3:length(smap_file)

    disp(j-2);

    gmap_name=strcat(gmap_path,num2str(j-2), '.jpg');

%     gmap_name=strcat(gmap_path,smap_file(j).name);

    smap_name=strcat(smap_path,num2str(j-2+ 0 ), '.jpg');

%     smap_name=strcat(smap_path,num2str(j-2+ 0 ), '_SaliencyMap', '.jpg');

    gmap=imresize(imread(gmap_name), [224, 224], 'bicubic');

    smap=imresize(imread(smap_name), [224, 224], 'bicubic');

    sal_map=mat2gray(smap);

    if gmap==0

        continue;

    end

    if size(gmap,3)==3

        gt_final_map=rgb2gray(gmap);

    else

        gt_final_map = gmap;

    end

    sal_map=imresize(sal_map,0.5);

    gt_final_map=imresize(gt_final_map,0.5);

    threshold_value = graythresh(gt_final_map);

    gt_final_map_bin = im2bw(gt_final_map, threshold_value);

    c = KLdiv(sal_map, gt_final_map);

    idx=find(isnan(c));

    c(idx)=0.5;

    c = abs(c);

    a(j-2,1)=mean(c);

end

% b(i-2,1)=mean(a);

% clear a;

% end

KLdiv = mean(a);