Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation

By Soong-Der Chen, A. Ramli. IEEE Trans. Consumer Electron., 2003

952 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/1cc375907980a466b9d74381519fa50530c8545b

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In Computer Vision and Pattern Recognition

Citations in the corpus

Contextual and Variational Contrast Enhancement (2011, background): “High contrast subblocks give a high EME ; (c) FHSABP ; (d) HMF ; (e) CEBGA ; and (f) CVC . value, whereas for homogeneous subblocks, the EME value should be close to zero.”
Gray-level grouping (GLG): an automatic method for optimized image contrast Enhancement-part I: the basic method (2006, methodology): “An extension of the basic GLG to local contrast enhancement approaches, adaptive gray-level grouping (A-GLG), will be presented in Section IV.”
Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement (2007, background): “For the implementation of RMSHE, we set the value of r equal to 3, where the histogram is divided into 8 sub-histograms, based on average values.”
A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement (2017, neutral): “…address the problem, many image enhancement techniques have been proposed including histogram-based methods [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13] , Retinex-based methods [14], [15], [16], [17], [18], [19], [20], Logarithmic Image Processing methods [21], [22], and…”
A Dynamic Histogram Equalization for Image Contrast Enhancement (2007, methodology): “2 shows the original image along with simulation results from GHE, LHE, DHS, RMSHE and DHE.”
Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving (2007, methodology): “B) proposed in [7], and named recursive mean-separate HE (RMSHE), proposes the following.”
Bi-histogram equalization with a plateau limit for digital image enhancement (2009, background): “However, some cases do require higher degree of preservation to avoid unpleasant artifacts [9].”
Brightness preserving histogram equalization with maximum entropy: a variational perspective (2005, methodology): “Histogram Equalization (RMSHE), has been proposed to preserve the brightness [ 6 ].”
An Experiment-Based Review of Low-Light Image Enhancement Methods (2020, methodology): “Based on BBHE and recursive mean-separate histogram equalization (RMSHE) [85], an LHE algorithm that maintains image brightness was proposed in [86].”