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Modeling the space of camera response functions.
IEEE Trans Pattern Anal Mach Intell. 2004 Oct; 26(10):1272-82.IT

Abstract

Many vision applications require precise measurement of scene radiance. The function relating scene radiance to image intensity of an imaging system is called the camera response. We analyze the properties that all camera responses share. This allows us to find the constraints that any response function must satisfy. These constraints determine the theoretical space of all possible camera responses. We have collected a diverse database of real-world camera response functions (DoRF). Using this database, we show that real-world responses occupy a small part of the theoretical space of all possible responses. We combine the constraints from our theoretical space with the data from DoRF to create a low-parameter empirical model of response (EMoR). This response model allows us to accurately interpolate the complete response function of a camera from a small number of measurements obtained using a standard chart. We also show that the model can be used to accurately estimate the camera response from images of an arbitrary scene taken using different exposures. The DoRF database and the EMoR model can be downloaded at http://www.cs.columbia.edu/CAVE.

Authors+Show Affiliations

Computer Science Department, Columbia University, New York, NY 10027, USA. mdog@cs.columbia.eduNo affiliation info available

Pub Type(s)

Comparative Study
Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Validation Study

Language

eng

PubMed ID

15641715

Citation

Grossberg, Michael D., and Shree K. Nayar. "Modeling the Space of Camera Response Functions." IEEE Transactions On Pattern Analysis and Machine Intelligence, vol. 26, no. 10, 2004, pp. 1272-82.
Grossberg MD, Nayar SK. Modeling the space of camera response functions. IEEE Trans Pattern Anal Mach Intell. 2004;26(10):1272-82.
Grossberg, M. D., & Nayar, S. K. (2004). Modeling the space of camera response functions. IEEE Transactions On Pattern Analysis and Machine Intelligence, 26(10), 1272-82.
Grossberg MD, Nayar SK. Modeling the Space of Camera Response Functions. IEEE Trans Pattern Anal Mach Intell. 2004;26(10):1272-82. PubMed PMID: 15641715.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Modeling the space of camera response functions. AU - Grossberg,Michael D, AU - Nayar,Shree K, PY - 2005/1/12/pubmed PY - 2005/2/11/medline PY - 2005/1/12/entrez SP - 1272 EP - 82 JF - IEEE transactions on pattern analysis and machine intelligence JO - IEEE Trans Pattern Anal Mach Intell VL - 26 IS - 10 N2 - Many vision applications require precise measurement of scene radiance. The function relating scene radiance to image intensity of an imaging system is called the camera response. We analyze the properties that all camera responses share. This allows us to find the constraints that any response function must satisfy. These constraints determine the theoretical space of all possible camera responses. We have collected a diverse database of real-world camera response functions (DoRF). Using this database, we show that real-world responses occupy a small part of the theoretical space of all possible responses. We combine the constraints from our theoretical space with the data from DoRF to create a low-parameter empirical model of response (EMoR). This response model allows us to accurately interpolate the complete response function of a camera from a small number of measurements obtained using a standard chart. We also show that the model can be used to accurately estimate the camera response from images of an arbitrary scene taken using different exposures. The DoRF database and the EMoR model can be downloaded at http://www.cs.columbia.edu/CAVE. SN - 0162-8828 UR - https://www.unboundmedicine.com/medline/citation/15641715/Modeling_the_space_of_camera_response_functions_ DB - PRIME DP - Unbound Medicine ER -