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Perceptually aware image inpainting
Image inpainting is a process of reconstructing missing regions, or removing unwanted
objects automatically by propagating intensity and texture information from surrounding …
objects automatically by propagating intensity and texture information from surrounding …
Turning diffusion-based image colorization into efficient color compression
The work of Levin et al.(2004) popularized stroke-based methods that add color to gray
value images according to a small amount of user-specified color samples. Even though …
value images according to a small amount of user-specified color samples. Even though …
Survey on diverse image inpainting using diffusion models
S Parida, V Srinivas, B Jain, R Naik… - 2023 2nd International …, 2023 - ieeexplore.ieee.org
Image inpainting (or Image completion) is the process of reconstructing lost or corrupted
parts of images. It can be used to fill in missing or corrupted parts of an image, such as …
parts of images. It can be used to fill in missing or corrupted parts of an image, such as …
Adaptive curvature-guided image filtering for structure+ texture image decomposition
A preliminary structure+ texture image decomposition is very useful for a number of digital
image processing tasks, as different strategies are supposed to be employed for processing …
image processing tasks, as different strategies are supposed to be employed for processing …
Optimising spatial and tonal data for PDE-based inpainting
Some recent methods for lossy signal and image compression store only a few selected
pixels and fill in the missing structures by inpainting with a partial differential equation (PDE) …
pixels and fill in the missing structures by inpainting with a partial differential equation (PDE) …
Sparse inpainting with smoothed particle hydrodynamics
Digital image inpainting refers to techniques used to reconstruct a damaged or incomplete
image by exploiting available image information. The main goal of this work is to perform the …
image by exploiting available image information. The main goal of this work is to perform the …
Optimising data for exemplar-based inpainting
Optimisation of inpainting data plays an important role in inpainting-based codecs. For
diffusion-based inpainting, it is well-known that a careful data selection has a substantial …
diffusion-based inpainting, it is well-known that a careful data selection has a substantial …
Learning reaction-diffusion models for image inpainting
In this paper we present a trained diffusion model for image inpainting based on the
structural similarity measure. The proposed diffusion model uses several parametrized …
structural similarity measure. The proposed diffusion model uses several parametrized …
An Analysis of Generative Methods for Multiple-Image Inpainting
Image inpainting refers to the restoration of an image with missing regions in a way that is
not detectable by the observer. The inpainting regions can be of any size and shape. This is …
not detectable by the observer. The inpainting regions can be of any size and shape. This is …
From optimised inpainting with linear PDEs towards competitive image compression codecs
For inpainting with linear partial differential equations (PDEs) such as homogeneous or
biharmonic diffusion, sophisticated data optimisation strategies have been found recently …
biharmonic diffusion, sophisticated data optimisation strategies have been found recently …