In this project, I used image processing techniques to take the digitized Prokudin-Gorskii glass plate images and automatically produce a color image out of it. I first extracted the three color channel images, then place them on top of each other, and align them so that they form a single RGB color image. I also implemented image pyramid and edge detection techniques to improve the quality of color images.
As for higher resolution images, simple image aligning becomes extremely slow and inefficient. Therefore, I used image pyramid technique on top of image aligning, which significantly speeded up the process.
Red Offset: (3, 12) Green Offset: (2, 5) |
Red Offset: (2, 3) Green Offset: (2, -3) |
Red Offset: (3, 7) Green Offset: (3, 3) |
Red Offset: (-11, 103) Green Offset: (-11, 39) |
Red Offset: (2, 116) Green Offset: (17, 63) |
Red Offset: (22, 86) Green Offset: (14, 47) |
Red Offset: (23, 119) Green Offset: (14, 55) |
Red Offset: (15, 111) Blue Offset: (-30, 110) |
Red Offset: (41, 93) Green Offset: (31, 55) |
Red Offset: (34, 100) Green Offset: (20, 45) |
Red Offset: (15, 103) Blue Offset: (-34, -94) |
Red Offset: (20, 116) Green Offset: (20, 57) |
Red Offset: (33, 95) Green Offset: (-6, 47) |
Red Offset: (-18, 105) Green Offset: (-1, 63) |
Red Offset: (-27, 111) Green Offset: (-19, 55) |
Red Offset: (-18, 79) Green Offset: (-22, 4) |
Red Offset: (-1, 71) Green Offset: (-38, -70) |
Due to the differnet brighness values of the Emir image, simply using image alignment through color channels does not work. Therefore, I used Canny Edge Detection as a new image alignment feature. Instead of passing in color channels to find the best alignment, I applied edge detection on green/red images, and compare with the edge detected blue image. As shown below, the quality of alignment is significantly improved.
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