interp2may be useful here. Use the data as key points, then create a thinner grid of points that are the same width and height and are interpolated between the key points.
Something like that:
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data = [1 1 1 1 1 1 1 1 1 1; 1 1.04 1.04 1.04 1.03 1 1.01 1.01 1.03 1.01; 1.36 1.3 1.25 1.2 1.15 1.1 1.2 1.13 1.07 1.11; 3.65 3.16 2.94 2.68 2.39 2.22 2.17 1.95 1.79 1.81; 5.91 5.75 5.47 5.3 4.98 4.79 4.62 4.55 4.38 4.19; 6 6 5.99 5.83 5.49 5.33 5.14 4.94 4.77 4.74];
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[X,Y] = meshgrid(1:size(data,2), 1:size(data,1));
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[X2,Y2] = meshgrid(1:0.01:size(data,2), 1:0.01:size(data,1));
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outData = interp2(X, Y, data, X2, Y2, 'linear');
imagesc(outData);
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set(gca, 'XTick', linspace(1,size(X2,2),size(X,2)));
set(gca, 'YTick', linspace(1,size(X2,1),size(X,1)));
set(gca, 'XTickLabel', 1:size(X,2));
set(gca, 'YTickLabel', 1:size(X,1));
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colorbar;
The code below is required because defining a fine mesh ultimately increases the size of the image. I need to reclassify the axes in order to return to the original size.
:

MATLAB R2014a, - . R2014b +, - parula. , , .