paper-with-me

홈 › Papers

Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging Problems

2018-04-06 · Franziska Schirrmacher, Thomas Köhler, Christian Riess

Inverse problems play a central role for many classical computer vision and image processing tasks. Many inverse problems are ill-posed, and hence require a prior to regularize the solution space. However, many of the existing priors, like total variation, are based on ad-hoc assumptions that have difficulties to represent the actual distribution of natural images. Thus, a key challenge in research on image processing is to find better suited priors to represent natural images. In this work, we propose the Adaptive Quantile Sparse Image (AQuaSI) prior. It is based on a quantile filter, can be used as a joint filter on guidance data, and be readily plugged into a wide range of numerical optimization algorithms. We demonstrate the efficacy of the proposed prior in joint RGB/depth upsampling, on RGB/NIR image restoration, and in a comparison with related regularization by denoising approaches.

📄 PDF Abstract BibTeX arXiv:1804.02152

Code (1)

franziska-schirrmacher/AQuaSI 공식 구현

Tasks

DenoisingImage Restoration

Similar Papers 제목 키워드 기반

AquaSignal: An Integrated Framework for Robust Underwater Acoustic Analysis

2025-05-20 · Eirini Panteli, Paulo E. Santos, Nabil Humphrey

This paper presents AquaSignal, a modular and scalable pipeline for preprocessing, denoising, classification, and novelty detection of underwater acoustic signals. Designed to operate effectively in noisy and dynamic mar…

DenoisingNovelty Detection

Sequential sparse Gaussian process quantile regression

2026-06-30 · Hugo Nicolas, Olivier Le Maître arxiv

Quantile regression aims to estimate the conditional quantiles of a response variable from observed data. In a Bayesian setting, Gaussian process quantile regression provides uncertainty quantification but faces signific…

Temporal and volumetric denoising via quantile sparse image prior

2018-02-12 · Franziska Schirrmacher, Thomas Köhler, Tobias Lindenberger, Lennart Husvogt 외

This paper introduces an universal and structure-preserving regularization term, called quantile sparse image (QuaSI) prior. The prior is suitable for denoising images from various medical imaging modalities. We demonstr…

Computed Tomography (CT)Denoising

AquaSight: Automatic Water Impurity Detection Utilizing Convolutional Neural Networks

2019-07-17 · Ankit Gupta, Elliott Ruebush

According to the United Nations World Water Assessment Programme, every day, 2 million tons of sewage and industrial and agricultural waste are discharged into the worlds water. In order to address this pervasive issue o…

QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

2017-03-08 · Franziska Schirrmacher, Thomas Köhler, Lennart Husvogt, James G. Fujimoto 외

Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise. This paper introduces a spatio-temporal denoising algorithm for OCT …

DenoisingDiagnostic