image decomposition python

Innocent Iguana answered on May 6, 2023 Popularity 1/10 Helpfulness 8/10

answer image decomposition python

image decomposition python

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# Singular value decomposition
U, s, V = np.linalg.svd(image_gray , full_matrices=True)
# Convert s to diagnal matrix S
S = np.zeros((im_gray.shape[0], im_gray.shape[1]))
S[:image.shape[0], :image.shape[0]] = np.diag(s)
# Reproduce entire image
B = S.dot(V)
reproduced_img = U.dot(B)
# Test : check different no of components and outcomes
for n_component in [1,10,100,200, 500]:
    S_new = S[:, :n_component]
    V_new = V[:n_component, :]
    A = U.dot(S_new.dot(V_new))
    plt.imshow(A,cmap='gray')
    plt.title("Number of Components:"+str(n_component))
    plt.show()

Popularity 1/10 Helpfulness 8/10 Language python

Source: Grepper

Tags: decomposition image python

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Contributed on May 06 2023

Innocent Iguana

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image decomposition python

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