To reduce cost, many digital cameras use a single sensor array instead of using
three arrays for the red, green and blue. Thus at each pixel location only the red,
green or blue intensity value is available. And to generate a complete color image,
the camera must estimate the missing two values at each pixel location .Color filter
arrays are used to capture only one portion of the spectrum (Red, Green or Blue) at
each location. Various arrangements of the Color Filter Array (CFA) are possible, but
the Bayer array is the most commonly used arrangement and we will deal exclusively
with the Bayer array in this thesis.
Since each of the three colors channels are effectively downsampled, it leads to
aliasing artifacts. This thesis will analyze the effects of aliasing in the frequency-
domain and present a method to reduce the deterioration in image quality due to
aliasing artifacts.
Two reference algorithms, AH-POCS (Adams and Hamilton - Projection Onto
Convex Sets) and Adaptive Homogeneity-Directed interpolation, are discussed in de-
tail. Both algorithms use the assumption that there is high correlation in the high-
frequency regions to reduce aliasing. AH-POCS uses alias cancellation technique to
reduce aliasing in the red and blue images, while the Adaptive Homogeneity-Directed
interpolation algorithm is an edge-directed algorithm. We present here an algorithm
that combines these two techniques and provides a better result on average when
compared to the reference algorithms.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/22542 |
| Date | 31 March 2008 |
| Creators | Appia, Vikram V. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0024 seconds