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Journal ArticleDOI

A simple and effective histogram equalization approach to image enhancement

Heng-Da Cheng, +1 more
- 01 Mar 2004 - 
- Vol. 14, Iss: 2, pp 158-170
TLDR
The multi-peak generalized histogram equalization (multi-peak GHE) is proposed, which is improved by using multi- peak histogramequalization combined with local information to enhance the images effectively.
About: 
This article is published in Digital Signal Processing.The article was published on 2004-03-01. It has received 306 citations till now. The article focuses on the topics: Adaptive histogram equalization & Histogram matching.

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Citations
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Journal ArticleDOI

LIME: Low-Light Image Enhancement via Illumination Map Estimation

TL;DR: Experiments on a number of challenging low-light images are present to reveal the efficacy of the proposed LIME and show its superiority over several state-of-the-arts in terms of enhancement quality and efficiency.
Journal ArticleDOI

LLNet: A deep autoencoder approach to natural low-light image enhancement

TL;DR: In this paper, a deep autoencoder-based approach is proposed to identify signal features from low-light images and adaptively brighten images without over-amplifying/saturating the lighter parts in images with high dynamic range.
Posted Content

LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement

TL;DR: It is shown that a variant of the stacked-sparse denoising autoencoder can learn from synthetically darkened and noise-added training examples to adaptively enhance images taken from natural low-light environment and/or are hardware-degraded.
Journal ArticleDOI

Automated breast cancer detection and classification using ultrasound images: A survey

TL;DR: Generally, a CAD system consists of four stages: preprocessing, segmentation, feature extraction and selection, and classification, and their advantages and disadvantages are discussed.
Journal ArticleDOI

Approaches for automated detection and classification of masses in mammograms

TL;DR: The methods for mass detection and classification for breast cancer diagnosis are discussed, and their advantages and drawbacks are compared.
References
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Journal ArticleDOI

Adaptive histogram equalization and its variations

TL;DR: It is concluded that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clip ahe can be made adequately fast to be routinely applied in the normal display sequence.
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Contrast enhancement using brightness preserving bi-histogram equalization

TL;DR: It is shown mathematically that the proposed algorithm preserves the mean brightness of a given image significantly well compared to typical histogram equalization while enhancing the contrast and, thus, provides a natural enhancement that can be utilized in consumer electronic products.
Journal ArticleDOI

Image enhancement based on equal area dualistic sub-image histogram equalization method

TL;DR: The simulation results indicate that the algorithm can not only enhance the image information effectively but also preserve the original image luminance well enough to make it possible to be used in a video system directly.
Journal ArticleDOI

Adaptive image contrast enhancement using generalizations of histogram equalization

TL;DR: A scheme for adaptive image-contrast enhancement based on a generalization of histogram equalization (HE), which can produce a range of degrees of contrast enhancement, at one extreme leaving the image unchanged, at another yielding full adaptive equalization.
Journal ArticleDOI

Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms.

TL;DR: The selected CLAHE settings should be tested in the clinic with digital mammograms to determine whether detection of spiculations associated with masses detected at mammography can be improved.
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