Abstract
High Dynamic Range Images provide a more detailed information and their use in Computer Vision tasks is therefore desirable. However, the illumination distribution over the image often makes this kind of images difficult to use with common vision algorithms. In particular, the highlights and shadow parts in a HDR image are difficult to analyze in a standard way. In this paper, we propose a method to solve this problem by applying a preliminary step where we precisely compute the illumination distribution in the image. Having access to the illumination distribution allows us to subtract the highlights and shadows from the original image, yielding a material color image. This material color image can be used as input for standard computer vision algorithms, like the SIFT point matching algorithm and its variants.
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Cui, Y., Pagani, A., Stricker, D. (2011). Robust Point Matching in HDRI through Estimation of Illumination Distribution. In: Mester, R., Felsberg, M. (eds) Pattern Recognition. DAGM 2011. Lecture Notes in Computer Science, vol 6835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23123-0_23
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DOI: https://doi.org/10.1007/978-3-642-23123-0_23
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