Contrast limited histogram equalisation revisited

Mcvey, Jake (2022) Contrast limited histogram equalisation revisited. Doctoral thesis, University of East Anglia.

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Histogram based tone adjustment algorithms have been used in a number of different computer vision applications in the recent years. One of the primary benefits of using the image histogram to derive the tone curve to enhance an image, is that it ensures the scene contents drives the enhancement i.e., each image has a unique tone curve.

Perhaps the most well known image enhancement algorithm, Histogram Equalisation (HE), is a contrast adjustment algorithm that uses the image histogram, directly, to define a tone curve that brings out image details. However, HE often makes tone curves with large slopes that generate unpleasing reproductions. Contrast Limited Histogram Equalisation (CLHE) builds naturally upon HE and constrains the slopes of the tone curve such that the reproductions look better. Indeed, in almost all cases CLHE is preferred to HE.

In this thesis we explore the CLHE algorithm in detail and highlight the shortcomings of the algorithm. We explore and discuss several approaches aimed at overcoming the limitations of CLHE, while also considering modern histogram based tone adjustment algorithms. The work in this thesis is motivated by the fact that CLHE is very popular in the modern literature. CLHE also - due to it’s inclusion in the Apical Iridix tone mapper - ships in many thousands of cameras.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Computing Sciences
Depositing User: Nicola Veasy
Date Deposited: 26 Jun 2024 13:48
Last Modified: 26 Jun 2024 13:48


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