1 code implementation • NeurIPS 2021 • Ali Hashemi, Yijing Gao, Chang Cai, Sanjay Ghosh, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe
Several problems in neuroimaging and beyond require inference on the parameters of multi-task sparse hierarchical regression models.
1 code implementation • 22 Dec 2020 • Sanjay Ghosh, Arpan Garai
In this work, we present a new downscaling technique which is based on kernel-based image filtering concept.
no code implementations • 18 Jan 2019 • Unni V. S., Sanjay Ghosh, Kunal. N. Chaudhury
In plug-and-play image restoration, the regularization is performed using powerful denoisers such as nonlocal means (NLM) or BM3D.
no code implementations • 26 Oct 2017 • Sanjay Ghosh, Kunal. N. Chaudhury
To bypass this, the authors proposed a separable approximation in which the image rows and columns are filtered using lifting.
no code implementations • 28 Jan 2017 • Sanjay Ghosh, Amit K. Mandal, Kunal. N. Chaudhury
In Non-Local Means (NLM), each pixel is denoised by performing a weighted averaging of its neighboring pixels, where the weights are computed using image patches.
no code implementations • 7 May 2016 • Sanjay Ghosh, Kunal. N. Chaudhury
In this paper, we consider a natural extension of the edge-preserving bilateral filter for vector-valued images.
no code implementations • 7 May 2016 • Sanjay Ghosh, Kunal. N. Chaudhury
A direct implementation of the Gaussian bilateral filter requires $O(\sigma_s^2)$ operations per pixel, where $\sigma_s$ is the standard deviation of the spatial Gaussian.
no code implementations • 26 Mar 2016 • Sanjay Ghosh, Kunal. N. Chaudhury
By controlling the cardinality of the Fourier basis, we can obtain a good tradeoff between the run-time and the filtering accuracy.