Project 1: Image Filtering and Hybrid Images

In this project, I implenment a image filter, then use it to create hybrid images.

Image Filter


%my_imfilter
[m,n,o]=size(image);
    [a,b]=size(filter);
    a=(a-1)/2;
    b=(b-1)/2;
    A=padarray(image,[a,b],'symmetric');
    output=zeros(size(A));
    for k=1:o
        for i=a+1:a+m
            for j=b+1:b+n
                output(i,j,k)=sum(sum(A(i-a:i+a,j-b:j+b,k).*filter));
            end
        end
    end
    output=output(a+1:a+m,b+1:b+n,:);

inner two loops to compute each elements in the result matrix by summing the dot product of filter with same size of image matrix centered at correasponding entry. For boraders, I pad the orginal image with symmetric padding with width related to filter size.

the outer loop computes the image in different color channels then combine them to produce a new image.

Results of my_imfilter

orginal image

identity filter

blur filter

1d Gaussian Filter

sobel_filter

laplacian_filter

orginal-blur

Hybrid Image


%my_imfilter
cutoff_frequency = 7
low_frequencies = my_imfilter(image1,filter);
high_frequencies = image2-my_imfilter(image2,filter);
hybrid_image = low_frequencies+high_frequencies;

low frequency image is the result of applying Gaussian filter to image1

high frequency image is the result of image2 subtract Gaussian filtered image2

hybrid_image is the sum of two filtered images.

cat and dog, cutoff_frequency=7

low_frequencies

high_frequencies

hybrid_image

hybrid_image_scales
marilyn and einstein, cutoff_frequency=3

low_frequencies

high_frequencies

hybrid_image

hybrid_image_scales
submarine and fish, cutoff_frequency=3

low_frequencies

high_frequencies

hybrid_image

hybrid_image_scales