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Sensitivity and Resolution Improvement in RGBW Color Filter Array Sensor.

Seunghoon Jee¹, Ki Sun Song², Moon Gi Kang³

¹Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei Road, Seodaemun-gu, Seoul 03722, Korea. jeedang1109@hanmail.net.

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|June 9, 2018

Summary

This summary is machine-generated.

This study introduces a new post-processing method for red-green-blue-white (RGBW) color filter arrays (CFAs). The technique enhances image resolution and red-green-blue (RGB) channel sensitivity by updating white (W) channel texture components.

Keywords:

color filter array demosaicing red-green-blue-white (RGBW)resolution improvement sensitivity improvement texture decomposition

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Area of Science:

Image processing
Computational imaging
Color filter array design

Background:

Red-green-blue-white (RGBW) color filter arrays (CFAs) offer high sensitivity but suffer from spatial resolution degradation.
Existing RGBW CFA demosaicing methods struggle to improve red-green-blue (RGB) channel sensitivity to the white (W) channel level.

Purpose of the Study:

To propose a novel demosaiced image post-processing method to enhance RGBW CFA sensitivity and resolution.
To improve the spatial resolution and color channel sensitivity of images captured with RGBW CFAs.

Main Methods:

A post-processing method is proposed that decomposes texture components, including noise and resolution information.
A cross multilateral filter (CMF) is introduced to decompose smoothness and texture components using color difference information.
The method updates the W channel texture component with RGB channel textures to improve sensitivity and resolution.

Main Results:

The proposed method effectively decomposes texture components, luminance noise, color noise, and color aliasing artifacts.
Updating RGB channels with W channel texture components significantly improves sensitivity and resolution.
The signal-to-noise ratio (SNR) improved by approximately 4.5 dB, maintaining W pixel resolution characteristics.

Conclusions:

The developed post-processing algorithm successfully enhances RGBW CFA sensitivity and resolution.
The cross multilateral filter (CMF) is effective in decomposing image components for improved image quality.
The method offers a viable solution for overcoming spatial resolution limitations in RGBW CFA imaging.