Recursive sub-image histogram equalization applied to gray scale images

By K. S. Sim, C. P. Tso, Y. Y. Tan. Pattern Recognition Letters, 2007

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Bi-histogram equalization with a plateau limit for digital image enhancement (2009, background): “For the implementation of both RMSHE and RSIHE, we set the recursion level (i.e. r) to be equal to two.”
Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution (2013, methodology): “Therefore, the BBHE, DSIHE, and RSIHE methods failed again to enhance the contrast, as displayed in Fig.”
An Experiment-Based Review of Low-Light Image Enhancement Methods (2020, methodology): “Other typical algorithms include gain-controllable clipped histogram equalization (GCCHE) [72], recursive subimage histogram equalization (RSIHE) [92], entropy-based dynamic subhistogram equalization (EDSHE) [93], dynamic histogram equalization (DHE) [94], brightness-preserving dynamic histogram…”
Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement (2008, methodology): “[5] generalized DSIHE into RSIHE (Recursive Sub-Image Histogram Equalization).”
Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement (2007, methodology): “Sim et al [8] propose a similar method to RMSHE known as recursive sub-image histogram equalization (RSIHE).”