Active Short-Long Exposure Deblurring

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

Abstrakti

Mobile phones can capture image bursts to produce high quality still photographs. The simplest form of a burst is two frame short-long (S-L) exposure. S-L exposure is particularly suitable in low light conditions where short exposure frames are sharp but noisy and dark, and long exposure frames are affected by motion blur but have better scene chromaticity and luminance. In this work, we take a step further and define active short-long exposure deblurring where the viewfinder frames before the burst are used to optimize the S-L exposure parameters. We introduce deep architectures and data generation for active S-L exposure deblurring. The approach is experimentally validated with realistic data and it shows clear improvements. For the most difficult scenes (worst 5%) the PSNR is improved by +1.39dB.

AlkuperäiskieliEnglanti
Otsikko2022 26th International Conference on Pattern Recognition, ICPR 2022
KustantajaIEEE
Sivut281-287
Sivumäärä7
ISBN (elektroninen)9781665490627
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Pattern Recognition - Montreal, Kanada
Kesto: 21 elok. 202225 elok. 2022

Julkaisusarja

NimiProceedings - International Conference on Pattern Recognition
Vuosikerta2022-August
ISSN (painettu)1051-4651

Conference

ConferenceInternational Conference on Pattern Recognition
Maa/AlueKanada
KaupunkiMontreal
Ajanjakso21/08/2225/08/22

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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