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Journal ArticleDOI

Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution

TLDR
An automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels and uses temporal information regarding the differences between each frame to reduce computational complexity is presented.
Abstract
This paper proposes an efficient method to modify histograms and enhance contrast in digital images. Enhancement plays a significant role in digital image processing, computer vision, and pattern recognition. We present an automatic transformation technique that improves the brightness of dimmed images via the gamma correction and probability distribution of luminance pixels. To enhance video, the proposed image-enhancement method uses temporal information regarding the differences between each frame to reduce computational complexity. Experimental results demonstrate that the proposed method produces enhanced images of comparable or higher quality than those produced using previous state-of-the-art methods.

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Citations
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Journal ArticleDOI

Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images

TL;DR: This paper proposes to use the convolutional neural network (CNN) to train a SICE enhancer, and builds a large-scale multi-exposure image data set, which contains 589 elaborately selected high-resolution multi-Exposure sequences with 4,413 images.
Journal ArticleDOI

The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement

TL;DR: A novel reduced-reference image quality metric for contrast change (RIQMC) is presented using phase congruency and statistics information of the image histogram and results justify the superiority and efficiency of RIQMC over a majority of classical and state-of-the-art IQA methods.
Journal ArticleDOI

Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data

TL;DR: A new no-reference (NR) IQA model is developed and a robust image enhancement framework is established based on quality optimization, which can well enhance natural images, low-contrast images,Low-light images, and dehazed images.
Journal ArticleDOI

Contrast Enhancement-Based Forensics in Digital Images

TL;DR: This paper proposes two novel algorithms to detect the contrast enhancement involved manipulations in digital images, focusing on the detection of global contrast enhancement applied to the previously JPEG-compressed images, which are widespread in real applications.
Journal ArticleDOI

An adaptive gamma correction for image enhancement

TL;DR: An adaptive gamma correction (AGC) is proposed to appropriately enhance the contrast of the image where the parameters of AGC are set dynamically based on the image information.
References
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Journal ArticleDOI

FSIM: A Feature Similarity Index for Image Quality Assessment

TL;DR: A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features.
Journal ArticleDOI

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

A Histogram Modification Framework and Its Application for Image Contrast Enhancement

TL;DR: A general framework based on histogram equalization for image contrast enhancement, and a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.
Journal ArticleDOI

Image enhancement via adaptive unsharp masking

TL;DR: A new method for unsharp masking for contrast enhancement of images is presented that employs an adaptive filter that controls the contribution of the sharpening path in such a way that contrast enhancement occurs in high detail areas and little or no image sharpening occurs in smooth areas.
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