International Conference on Emerging Technology Trends |
Foundation of Computer Science USA |
ICETT2011 - Number 1 |
None 2011 |
Authors: Divya S |
0e84ffc9-5ab2-4749-ba7a-8f9fc45e0dd9 |
Divya S . Sharp Color Edge Preservation using HOI. International Conference on Emerging Technology Trends. ICETT2011, 1 (None 2011), 1-6.
Color Filter Array Demosaicking is an interpolation process to determine missing color pixel values when a single-sensor digital camera is used for color image capture. This paper focuses on sharp color edge preservation of demosaicked image using a second order interpolation technique. Several demosaicking methods have already been developed, e.g., Bi linear, Constant-Hue-Based, Edge-Directed etc. Here, a new method based on the application of Taylor series is proposed. The missing green values are interpolated using Taylor series expansion because of its accuracy and simplicity. Color edges are sharp boundaries between two distinct colors. To avoid the blurring of an edge, interpolants are first estimated in four opposite directions so that no interpolation is carried out across an edge. Then a classifier based on an edge orientation map is used to assign weights for a edge preserving weighted median filter, which is used to determine the output. Weighted median filter is used to produce an output from the four interpolants in order to preserve sharp color edges and produce minimal color artifacts in the output image. Thus, the estimates obtained are more accurate than already existing methods due to the inclusion of higher-order terms. The spectral correlations refer to the fact there is a high correlation between the green and red/blue pixel values within a local neighborhood. Higher order approximation is required for the green plane only .For red and blue planes, first-order approximation is adequate because they are under sampled and the human visual system is less sensitive to red and blue. So first-order interpolation is sufficient. It has been shown that proposed method outperforms visually and quantitatively with image quality measures, when compared with other existing methods.