Blind inverse gamma correction

By Hany Farid. IEEE Transactions on Image Processing, 2001

392 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Atomic and Molecular Physics, and Optics, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/6152d79bebb6ae7d671c8e7846a53901a6e4134f

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In Analytical Chemistry

In Atomic and Molecular Physics, and Optics

In Industrial and Manufacturing Engineering

Citations in the corpus

Modeling inter-camera space-time and appearance relationships for tracking across non-overlapping views (2008, background): “This issue is discussed in the next two sections.”
Forensic detection of image manipulation using statistical intrinsic fingerprints (2010, methodology): “Prior work which identifies image tampering by detecting operation specific fingerprints includes the detection of resampling [13], double JPEG compression [14]–[16], as well as the parameterization of gamma correction [17].”
Determining the Camera Response from Images: What Is Knowable? (2003, methodology): “When we refer to “chartless” methods, we do not include Farid’s method [9].”
Digital image forensics via intrinsic fingerprints (2008, background): “The CFA pattern and the color interpolation coefficients can be jointly estimated from the output image [33].”
Contextual Priming for Object Detection (2003, methodology): “The use of such regularities in the statistics finds applications in models of neural coding (Field, 1987), lightness and reflectance perception (Weiss, 2001; Dror, 2001), and camera distortion removal (Farid, 2001 ) among many other applications.”
Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis (2009, background): “This paper contributes by addressing such a difficult problem in computational photography and vision, and provides the first fast, fully-automatic, and fine-grained algorithm to detect tampered JPEG images.”
High Dynamic Range Imaging (2015, background): “Farid [44] proposes a more principled approach in which the gamma value can be blindly estimated in the absence of any camera calibration information based on the single image (the so-called blind inverse gamma correction).”
Appearance modeling for tracking in multiple non-overlapping cameras (2005, background): “Many authors have approximated the radiometric response function of a camera by a gamma function [4, 11], i.”
Statistical Tools for Digital Forensics (2004, methodology): “We have previously shown that higher order correlations introduced by a non-linear transformation are proportional to the value of the parameter γ [6].”
Modeling the space of camera response functions (2004, positive): “The single image recovery algorithm presented in [9] also assumes the response is a gamma curve.”