Gray and color image contrast enhancement by the curvelet transform

By Jean-Luc Starck, Fionn Murtagh, E.J. Candes, David L. Donoho. IEEE Transactions on Image Processing, 2003

585 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/23c5f46f7e780edd31158a894496c34c9bd94eba

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Citations in the corpus

The Curvelet Transform (2010, methodology): “The applications of the first-generation curvelets were extended to image contrast enhancement [62] and astronomical image representation [61] in 2003, and to fusion of satellite images [17] in 2005.”
Gray-level grouping (GLG): an automatic method for optimized image contrast Enhancement-part I: the basic method (2006, methodology): “In the next section, the principle and algorithm of the graylevel grouping technique will be described.”
Transforms and Operators for Directional Bioimage Analysis: A Survey. (2016, background): “2002), contrast enhancement (Starck et al. 2003), and reconstruction in limited-angle tomography (Frikel 2013).”
An Experiment-Based Review of Low-Light Image Enhancement Methods (2020, methodology): “[181] proposed a multiscale analysis method based on the curvelet transform and compared it with the WT algorithm to demonstrate its superiority for color image enhancement.”
Remote sensing image fusion using the curvelet transform (2007, methodology): “In particular, the curvelet transform, originally proposed for image denoising [14], has been found to be an invaluable tool for image enhancement [15].”
Retinal Image Analysis Using Curvelet Transform and Multistructure Elements Morphology by Reconstruction (2011, background): “m can be derived from maximum curvelet coefficients of the relative band MC (m = kMC ), or can be determined with regard to σji (m = kσji) [16].”
Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement (2010, background): “…(c) Enhancing result of (a) by multiscale wavelet transform-based algorithm [61], [62], (d) Enhancing result of (a) by contourlet-based algorithm [63], [64], (e) Enhancing result of (a) by nonlinear frequency enhancement algorithm [54], (f) 0.5-order fractional differential of (a), (g) Original…”
The Cosparse Analysis Model and Algorithms (2011, unknown): “Empirically, analysis models have been successfully used for a variety of signal processing tasks [24, 30, 48, 49, 50] such as denoising, deblurring, and most recently compressed sensing, but this has been done with little theoretical justification.”
Fusion of multispectral and panchromatic Satellite images using the curvelet transform (2005, methodology): “In this section, we review the theory of ridgelet and curvelet transforms, presented in [3]–[6], which will be used in the subsequent sections.”