Colorizing the Prokudin-Gorskii Photo Collection

For Fall 2024, I am taking an image processing class, and one assignment involves colorizing the historical Prokudin-Gorskii photo collection.

The approach involves splitting each image into its red, green, and blue channels and aligning them to form a full-color image. By iterating over offsets from -15 to 15 and computing the cross-correlation between channels, I could align most images accurately. For higher-resolution images, I implemented an image pyramid for faster alignment.

One challenging image featured a person seated in a chair. To address the alignment issues, I applied an edge detection filter to each channel, aligning the edges by maximizing normalized covariance.

Here’s the result of edge detection on the challenging photo:

Before:

After Alignment:

Low-Resolution Results

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Here are some low-resolution images, with their respective offset values for the green and red channels (in the format (offsetX_g, offsetY_g), (offsetX_r, offsetY_r)):

— Offset: (-3, 2) (3, 2)

— Offset: (3, 3) (6, 3)

— Offset: (5, 2) (12, 3)

High-Resolution Results

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For high-resolution images, offsets are applied progressively in an image pyramid (first multiplied by 16, then 8, then 4, and finally 1). Here are the high-resolution images before and after alignment:

Original Images:

Aligned Images:

Note: Some images, like Image 9, did not align well because the channels were not divided cleanly into thirds.

Calculated Offsets

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Here are the offsets used for aligning each high-resolution image.

For further details, you can view the code on GitHub.