851 research outputs found
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). Suitable operators include the Laplacian, the
biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The
quality of such approaches depends substantially on the selection of the data
that is kept. Optimising this data in the domain and codomain gives rise to
challenging mathematical problems that shall be addressed in our work.
In the 1D case, we prove results that provide insights into the difficulty of
this problem, and we give evidence that a splitting into spatial and tonal
(i.e. function value) optimisation does hardly deteriorate the results. In the
2D setting, we present generic algorithms that achieve a high reconstruction
quality even if the specified data is very sparse. To optimise the spatial
data, we use a probabilistic sparsification, followed by a nonlocal pixel
exchange that avoids getting trapped in bad local optima. After this spatial
optimisation we perform a tonal optimisation that modifies the function values
in order to reduce the global reconstruction error. For homogeneous diffusion
inpainting, this comes down to a least squares problem for which we prove that
it has a unique solution. We demonstrate that it can be found efficiently with
a gradient descent approach that is accelerated with fast explicit diffusion
(FED) cycles. Our framework allows to specify the desired density of the
inpainting mask a priori. Moreover, is more generic than other data
optimisation approaches for the sparse inpainting problem, since it can also be
extended to nonlinear inpainting operators such as EED. This is exploited to
achieve reconstructions with state-of-the-art quality.
We also give an extensive literature survey on PDE-based image compression
methods
Navigation domain representation for interactive multiview imaging
Enabling users to interactively navigate through different viewpoints of a
static scene is a new interesting functionality in 3D streaming systems. While
it opens exciting perspectives towards rich multimedia applications, it
requires the design of novel representations and coding techniques in order to
solve the new challenges imposed by interactive navigation. Interactivity
clearly brings new design constraints: the encoder is unaware of the exact
decoding process, while the decoder has to reconstruct information from
incomplete subsets of data since the server can generally not transmit images
for all possible viewpoints due to resource constrains. In this paper, we
propose a novel multiview data representation that permits to satisfy bandwidth
and storage constraints in an interactive multiview streaming system. In
particular, we partition the multiview navigation domain into segments, each of
which is described by a reference image and some auxiliary information. The
auxiliary information enables the client to recreate any viewpoint in the
navigation segment via view synthesis. The decoder is then able to navigate
freely in the segment without further data request to the server; it requests
additional data only when it moves to a different segment. We discuss the
benefits of this novel representation in interactive navigation systems and
further propose a method to optimize the partitioning of the navigation domain
into independent segments, under bandwidth and storage constraints.
Experimental results confirm the potential of the proposed representation;
namely, our system leads to similar compression performance as classical
inter-view coding, while it provides the high level of flexibility that is
required for interactive streaming. Hence, our new framework represents a
promising solution for 3D data representation in novel interactive multimedia
services
Gaining Insights into Denoising by Inpainting
The filling-in effect of diffusion processes is a powerful tool for various
image analysis tasks such as inpainting-based compression and dense optic flow
computation. For noisy data, an interesting side effect occurs: The
interpolated data have higher confidence, since they average information from
many noisy sources. This observation forms the basis of our denoising by
inpainting (DbI) framework. It averages multiple inpainting results from
different noisy subsets. Our goal is to obtain fundamental insights into key
properties of DbI and its connections to existing methods. Like in
inpainting-based image compression, we choose homogeneous diffusion as a very
simple inpainting operator that performs well for highly optimized data. We
propose several strategies to choose the location of the selected pixels.
Moreover, to improve the global approximation quality further, we also allow to
change the function values of the noisy pixels. In contrast to traditional
denoising methods that adapt the operator to the data, our approach adapts the
data to the operator. Experimentally we show that replacing homogeneous
diffusion inpainting by biharmonic inpainting does not improve the
reconstruction quality. This again emphasizes the importance of data adaptivity
over operator adaptivity. On the foundational side, we establish deterministic
and probabilistic theories with convergence estimates. In the non-adaptive 1-D
case, we derive equivalence results between DbI on shifted regular grids and
classical homogeneous diffusion filtering via an explicit relation between the
density and the diffusion time
Light field image processing : overview and research issues
Light field (LF) imaging first appeared in the computer graphics community with the goal of photorealistic 3D rendering [1]. Motivated by a variety of potential applications in various domains (e.g., computational photography, augmented reality, light field microscopy, medical imaging, 3D robotic, particle image velocimetry), imaging from real light fields has recently gained in popularity, both at the research and industrial level.peer-reviewe
Livrable D4.2 of the PERSEE project : Représentation et codage 3D - Rapport intermédiaire - Définitions des softs et architecture
51Livrable D4.2 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D4.2 du projet. Son titre : Représentation et codage 3D - Rapport intermédiaire - Définitions des softs et architectur
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