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Enhancing Photograph Visual Quality Using Texture and Contrast Data From Near Infra-red Images

机译:使用来自近红外图像的纹理和对比度数据提高照片的视觉质量

摘要

Near infra-red images of natural scenes usually have better contrast and contain rich texture details that may not be perceived in visible light photographs. The contrast and rich texture details form a NIR image corresponding to a visible light image are useful for enhancing the visual quality of the visible light image. To enhance the visual quality of a visible light image using its corresponding near infra-red image, a computer-implemented method computes a weight region mask from the visible light image, transfers contrast data and texture data from the near infra-red image to the visible light image guided by the weighted region mask. The contrast data is computed from the low frequency subbands of the visible light image and corresponding infra-red image after a wavelet transform by matching the histogram of gradient magnitude. The texture data is computed from the high frequency subbands of both images after wavelet transform.
机译:自然场景的近红外图像通常具有更好的对比度,并且包含丰富的纹理细节,而这些细节在可见光照片中可能无法感知。对比度和丰富的纹理细节形成了对应于可见光图像的NIR图像,可用于增强可见光图像的视觉质量。为了使用其对应的近红外图像增强可见光图像的视觉质量,计算机实现的方法从可见光图像计算权重区域蒙版,将对比度数据和纹理数据从近红外图像传输到图像。加权区域蒙版引导的可见光图像。通过匹配梯度幅度的直方图,在小波变换之后从可见光图像和对应的红外图像的低频子带计算对比度数据。根据小波变换后的两个图像的高频子带计算纹理数据。

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