Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generating Training Data for Denoising Real RGB Images via Camera
  Pipeline Simulation   Image reconstruction techniques such as denoising often need to be applied to
the RGB output of cameras and cellphones. Unfortunately, the commonly used
additive white noise (AWGN) models do not accurately reproduce the noise and
the degradation encountered on these inputs. This is particularly important for
learning-based techniques, because the mismatch between training and real world
data will hurt their generalization. This paper aims to accurately simulate the
degradation and noise transformation performed by camera pipelines. This allows
us to generate realistic degradation in RGB images that can be used to train
machine learning models. We use our simulation to study the importance of noise
modeling for learning-based denoising. Our study shows that a realistic noise
model is required for learning to denoise real JPEG images. A neural network
trained on realistic noise outperforms the one trained with AWGN by 3 dB. An
ablation study of our pipeline shows that simulating denoising and demosaicking
is important to this improvement and that realistic demosaicking algorithms,
which have been rarely considered, is needed. We believe this simulation will
also be useful for other image reconstruction tasks, and we will distribute our
code publicly.

17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph