Influence of Spectral Sensitivity Functions on color demosaicing
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Typical consumer cameras sense at each pixel only one out of the three color components the representation of a color image requires. Then the missing components are estimated via a procedure referred to as demosaicking. The recent spread of sparse regular ...
Finding relations between image semantics and image characteristics is a problem of long standing in computer vision and related fields. Despite persistent efforts and significant advances in the field, today’s computers are still strikingly unable to achi ...
A cost-effective and convenient approach for color imaging is to use a single sensor and mount a color filter array (CFA) in front of it, such that at each spatial position the scene information in only one color channel is captured. To estimate the missin ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2012
We present a method to automatically detect shadows in a fast and accurate manner by employing the inherent sensitivity of digital camera sensors to the near-infrared (NIR) part of the spectrum. Shadows are generally found in the dark parts of an image, be ...
Color image sensors use color filter arrays (CFA) to capture information at each sensor pixel position and require color demosaicing to reconstruct full color images. The quality of the demosaicked image is hindered by the sensor characteristics during the ...
Camera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, color rendering, and color constancy. In this paper, we aim ...
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Sensors of most digital cameras are made of silicon that is inherently sensitive to both the visible and near-infrared parts of the electromagnetic spectrum. In this paper, we address the problem of color and NIR joint acquisition. We propose a framework f ...
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