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In this paper, we utilize our recent Gramian-based filtering scheme to remove noise sampled from five prominent probability distributions from selected images. ... Current existing denoising methods have their own assumptions on the probability distribution in which the contaminated noise is sampled for the method to attain its expected denoising performance. ... In this paper, we examine the denoising performance of our GGD method, and apply it to images contaminated with five diverse noise types sampled from unique probability distributions. ...arXiv:2203.02600v1 fatcat:xsp5vb4alrasrksgrfokzwedze
To preserve image smoothness, this method inputs patches partitioned from the image rather than pixels. ... However, the quality of an image captured by a camera may be degraded by noise. Thus, some processing of images is required to filter out the noise without losing vital image features. ... We ran the same experiment for several realizations with different random seeds in the probability distribution that we sample the noise if the experiment is to test the influence of noise contamination ...arXiv:2010.07769v2 fatcat:cq5zatk25bga7iipv4tkfqkrce
From an analysis and controller design point of view, it is known that GSPT and its adaptation to control systems , provide mathematical tools to understand the dynamics, and design controllers from ... In a similar manner as for the linear case, we can compute a balanced realization from these two empirical Gramians. ... This is essentially done by finding the optimal sampling period (τ ) taking into account the probability distribution of the delay. ...doi:10.1137/18m1173460 fatcat:ytlzbwk7vbampbuyo6snenz33m