Abstract
We present a novel approach to description of a multidimensional image histogram insensitive with respect to an additive Gaussian noise in the image. The proposed quantities, although calculated from the histogram of the noisy image, represent the histogram of the original clear image. Noise estimation, image denoising and histogram deconvolution are avoided. We construct projection operators, that divide the histogram into non-Gaussian and Gaussian part, which is consequently removed to ensure the invariance. The descriptors are based on the moments of the histogram of the noisy image. The method can be used in a histogram-based image retrieval systems.
This work has been supported by the Czech Science Foundation (Grant No. GA18-07247S), by the Praemium Academiae, and by the Grant SGS18/188/OHK4/3T/14 provided by the Ministry of Education, Youth, and Sports of the Czech Republic (MŠMT ČR).
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Kostková, J., Flusser, J. (2019). Robust Histogram Estimation Under Gaussian Noise. In: Vento, M., Percannella, G. (eds) Computer Analysis of Images and Patterns. CAIP 2019. Lecture Notes in Computer Science(), vol 11678. Springer, Cham. https://doi.org/10.1007/978-3-030-29888-3_34
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