Color night vision equipment color enhancement method based on RGBW filter array

Abstract

The invention discloses a color night vision equipment color enhancement method based on an RGBW filter array, and belongs to the technical field of low-light night vision imaging and image processing. A four-channel automatic white balance algorithm based on gray world hypothesis is used to estimate light source color, brightness stretching is carried out on each channel image according to the maximum value of each channel pixel, and in consideration of color night vision noise distribution, image color cast caused by light source color temperature is recovered; the color components R, G, B and W are expanded to a nonlinear space, a loss function and a regression method are designed, a color card reference value under a standard light source and a color card sample value in a white balance correction image are used for training and solving a CCM parameter to minimize the loss function, and the image after color correction is obtained. According to the invention, the display degree, saturation degree and naturalness of the output color of the RGBW color night vision equipment can be improved, the application range is expanded, the color quality of the color night vision equipment in a low-illumination environment is improved, and the human eye observation comfort is improved.

Description

technical field [0001] The invention relates to a color enhancement method of a color night vision device, in particular to a color enhancement method of a color night vision device based on an RGBW filter array, and belongs to the technical field of low-light night vision imaging and image processing. Background technique [0002] In recent years, the solid-state color imaging technology based on the on-chip RGBW color filter array (Color Filter Array, CFA) has gradually expanded to the direction of low illumination. This type of imaging equipment uses high-performance CCD / CMOS as the core imaging component, which has the advantage of compact structure, and expands the minimum working illuminance of imaging equipment from the perspective of increasing the amount of incoming light. Compared with color equipment based on traditional Bayer arrays, the brightness and signal The noise ratio is significantly improved, and it is more suitable for application scenarios with illumin...

AI Technical Summary

Problems solved by technology

However, the color of the source image directly output by the color night vision device does not conform to the observation habits of the human eye. The overall shift of the image color; (b) the spectral response curve of the imaging device deviates from the CIE 1931XYZ standard observer spectral tri-stimulus value curve, resulting in differences between the source image color and the standard color; (c) the near-infrared spectral response part of the imaging device (780- 1100nm) interferes with the color components of the visible light part (380-780nm), and introduces a nonlinear color shift model, which reflects that the color saturation of the final imaging decreases, and the image looks dim, which is different from the color observed by the human eye under normal illumination. (d) The device source color and standard color cannot be guaranteed to be obtained under the same light source and the same illuminance, and the color components of different color spaces do not satisfy the linear transformation relationship, so that the linear color correction matrix commonly used in cameras (Color Correction Matrix, CCM) algorithm is no longer applicable

[0004] Due to the above reasons, the color enhancement method of the traditional color night vision equipment is no longer applicable to the color night vision equipment of the new RGBW filter array, and it needs to be specially designed for the color enhancement algorithm of the image signal processing (Image Signal Processing, ISP) module to improve The color quality of the output image finally conforms to the observation habits of the human eye

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