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An Acquisition Method for Visible and Near Infrared Images from Single CMYG Color Filter Array-Based Sensor

机译:基于单CMYG滤色器阵列传感器的可见和近红外图像的采集方法

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摘要

Near-infrared (NIR) images are very useful in many image processing applications, including banknote recognition, vein detection, and surveillance, to name a few. To acquire the NIR image together with visible range signals, an imaging device should be able to simultaneously capture NIR and visible range images. An implementation of such a system having separate sensors for NIR and visible light has practical shortcomings due to its size and hardware cost. To overcome this, a single sensor-based acquisition method is investigated in this paper. The proposed imaging system is equipped with a conventional color filter array of cyan, magenta, yellow, and green, and achieves signal separation by applying a proposed separation matrix which is derived by mathematical modeling of the signal acquisition structure. The elements of the separation matrix are calculated through color space conversion and experimental data. Subsequently, an additional denoising process is implemented to enhance the quality of the separated images. Experimental results show that the proposed method successfully separates the acquired mixed image of visible and near-infrared signals into individual red, green, and blue (RGB) and NIR images. The separation performance of the proposed method is compared to that of related work in terms of the average peak-signal-to-noise-ratio (PSNR) and color distance. The proposed method attains average PSNR value of 37.04 and 33.29 dB, respectively for the separated RGB and NIR images, which is respectively 6.72 and 2.55 dB higher than the work used for comparison.
机译:近红外线(NIR)图像在许多图像处理应用中非常有用,包括钞票识别,静脉检测和监视,以命名几个。为了将NIR图像与可见范围信号一起获取,成像装置应该能够同时捕获NIR和可见范围图像。由于其尺寸和硬件成本,这种具有用于NIR和可见光的单独传感器的这种系统的实现具有实用的缺点。为了克服这一点,本文研究了一种基于传感器的采集方法。所提出的成像系统配备有青色,品红色,黄色和绿色的传统滤色器阵列,并通过应用由信号采集结构的数学建模导出的所提出的分离矩阵来实现信号分离。通过颜色空间转换和实验数据计算分离矩阵的元素。随后,实施额外的去噪过程以增强分离图像的质量。实验结果表明,该方法成功将可见光和近红外信号的获取混合图像分离成单独的红色,绿色和蓝色(RGB)和NIR图像。该方法的分离性能与平均峰值信噪比(PSNR)和颜色距离的相关工作的分离性能。该方法分别达到分离的RGB和NIR图像的平均PSNR值为37.04和33.29dB,其分别比用于比较的工作的6.72和2.55dB。

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