Abstract

This paper proposes a novel way of combining color demosaicing and the auto white balance (AWB) method, which are important parts of image processing. Performance of the AWB is generally affected by demosaicing results because most AWB algorithms are performed posterior to color demosaicing. In this paper, in order to increase the performance and efficiency of the AWB algorithm, the color constancy problem is examined during the color demosaicing step. Initial estimates of the directional luminance and chrominance values are defined for estimating edge direction and calculating the AWB gain. In order to prevent color failure in conventional edge-based AWB methods, we propose a modified edge-based AWB method that used a predefined achromatic region. The estimation of edge direction is performed region adaptively by using the local statistics of the initial estimates of the luminance and chrominance information. Simulated and real Bayer color filter array (CFA) data are used to evaluate the performance of the proposed method. When compared to conventional methods, the proposed method shows significant improvements in terms of visual and numerical criteria.

Highlights

  • The PSNR and the normalized color difference (NCD) [36], which is an objective measure of the perceptual error between two color images, were used in order to measure the performance of the proposed algorithm quantitatively

  • A method of recovering white balanced and full color images from color sampled data was presented in this paper

  • In order to avoid the problem of treating these methods separately and increasing the computational efficiency, a simultaneous color demosaicing and automatic white balance (AWB) scheme was proposed

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Summary

Introduction

Since only one color component is available at each pixel, the other two missing color components have to be estimated from the neighboring pixels This process is referred to as CFA demosaicing or CFA interpolation. The color constancy property of the human visual system allows the perceived color to remain relatively constant at different color temperatures [2]. This capability is required for cameras to generate natural-looking images that match with human perception. The goal of the AWB method is to emulate human color constancy This is normally achieved by adjusting the image so that it looks as if it were taken under a canonical light (usually daylight)

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