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val += math.pow((pixel - mu), 2)
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return val / len(x)
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def _uicm(x):
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R = x[:, :, 0].flatten()
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G = x[:, :, 1].flatten()
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B = x[:, :, 2].flatten()
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RG = R - G
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YB = ((R + G) / 2) - B
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mu_a_RG = mu_a(RG)
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mu_a_YB = mu_a(YB)
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s_a_RG = s_a(RG, mu_a_RG)
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s_a_YB = s_a(YB, mu_a_YB)
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l = math.sqrt((math.pow(mu_a_RG, 2) + math.pow(mu_a_YB, 2)))
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r = math.sqrt(s_a_RG + s_a_YB)
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return (-0.0268 * l) + (0.1586 * r)
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def sobel(x):
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dx = ndimage.sobel(x, 0)
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dy = ndimage.sobel(x, 1)
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mag = np.hypot(dx, dy)
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mag *= 255.0 / np.max(mag)
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return mag
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def eme(x, window_size):
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"""
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Enhancement measure estimation
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x.shape[0] = height
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x.shape[1] = width
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"""
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# if 4 blocks, then 2x2...etc.
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k1 = x.shape[1] // window_size
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k2 = x.shape[0] // window_size
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# weight
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w = 2. / (k1 * k2)
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blocksize_x = window_size
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blocksize_y = window_size
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# make sure image is divisible by window_size - doesn't matter if we cut out some pixels
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x = x[:blocksize_y * k2, :blocksize_x * k1]
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val = 0
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for l in range(k1):
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for k in range(k2):
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block = x[k * window_size:window_size * (k + 1), l * window_size:window_size * (l + 1)]
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max_ = np.max(block)
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min_ = np.min(block)
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# bound checks, can't do log(0)
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if min_ == 0.0:
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val += 0
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elif max_ == 0.0:
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val += 0
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else:
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val += math.log(max_ / min_)
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return w * val
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def _uism(x):
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"""
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Underwater Image Sharpness Measure
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"""
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# get image channels
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R = x[:, :, 0]
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G = x[:, :, 1]
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B = x[:, :, 2]
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# first apply Sobel edge detector to each RGB component
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Rs = sobel(R)
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Gs = sobel(G)
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Bs = sobel(B)
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# multiply the edges detected for each channel by the channel itself
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R_edge_map = np.multiply(Rs, R)
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G_edge_map = np.multiply(Gs, G)
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B_edge_map = np.multiply(Bs, B)
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# get eme for each channel
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r_eme = eme(R_edge_map, 8)
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g_eme = eme(G_edge_map, 8)
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b_eme = eme(B_edge_map, 8)
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# coefficients
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lambda_r = 0.299
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lambda_g = 0.587
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lambda_b = 0.144
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return (lambda_r * r_eme) + (lambda_g * g_eme) + (lambda_b * b_eme)
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def plip_g(x, mu=1026.0):
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return mu - x
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def plip_theta(g1, g2, k):
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