• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.5C
• /
• pp.286-294
• /
• 2011

In most digital cameras, images are obtained by a sensor overlaid by the color filter array (CFA) such as Bayer, demanding a demosaicking procedure to rebuild the full resolution color images. However, due to the nature of sensor, it is necessary to consider denoising step to remove the noise. In this paper, we analyze demosaicking and denoising jointly and show that the proposed method can solve the denoising issue by simple manner, well suppress different level of noises. The proposed algorithm yields comparable performances measured by several image quality assessment (CPSNR, SCIELAB, and FSIM), while the computational cost is low.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.245-248
• /
• 2003

This parer proposes the six color separation using th color difference and granularity. Conventional method using the color difference increases the graininess in the bright region due to the usage of the cyan or magenta. To reduce the graininess in the bright region, we proposed the six color separation minimizing the graininess within the tolerance of the co]or difference. Initially, granularity is calculated based on the standard deviation of the lightness value and chrominance of the SCIELAB space and is applied to the six color separation using the color difference. Proposed six color separation using the color difference and granularity reduces the graininess in the bright region and obtains the smooth tone.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.51-59
• /
• 2004

This paper proposes an improved six-color separation reducing the graininess in a middle tone region based on the standard deviation of the lightness and chrominance in S-CIELAB space. Graininess is regarded as visual perception for the fluctuation of the lightness of the light cyan and cyan or light magenta and magenta. In the conventional methods, the granularity is extremely heuristic and inaccurate due to the use of the visual examination score. Accordingly, this paper proposes a method to calculate the objective granularity for six color separation. First, we use the lightness, redness-greenness, and yellowness-blueness of the S-CIELAB space reflecting the spatial-color sensitivity of the human and normalize the sum of the three standard deviations. Finally, we apply the proposed granularity to the six color separation after assigning the granularity to the lookup table and obtain the result reducing the graininess in a middle tone region.