Implementing Pseudocolor in Python: Examples with Matplotlib and OpenCV

Implementing Pseudocolor in Python: Examples with Matplotlib and OpenCV

1) Quick overview

• Pseudocolor maps single-channel (grayscale) data to color for better visual perception.
• Use Matplotlib for plotting and custom colormaps; use OpenCV for fast image-based applyColorMap / LUT operations.

2) Code examples

Matplotlib — simple pseudocolor (imshow + colormap)

python
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import numpy as np import matplotlib.pyplot as plt 
# sample data
data = np.random.randn(200, 200)
plt.imshow(data, cmap=‘viridis’, origin=‘lower’)
plt.colorbar()
plt.title(‘Pseudocolor with Matplotlib (viridis)’)
plt.show()

Common Matplotlib colormaps: ‘viridis’, ‘plasma’, ‘magma’, ‘inferno’, ‘cividis’, ‘jet’ (avoid for perceptual issues).

Matplotlib — custom colormap (linear segmented)

python
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import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import LinearSegmentedColormap 
cmap = LinearSegmentedColormap.from_list(‘mycmap’,
[(0.0, ’#000000’), (0.5, ’#ff0000’), (1.0, ’#ffff00’)])

data = np.linspace(0, 1, 256).reshape(16,16)
plt.imshow(data, cmap=cmap, origin=‘lower’)
plt.colorbar()
plt.title(‘Custom Matplotlib colormap’)
plt.show()

OpenCV — apply built-in colormap

”`python import cv2