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Journal ArticleDOI

Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images

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TLDR
Experimental results demonstrate that the proposed enhancement algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images.
Abstract
Image enhancement plays an important role in image processing and analysis. Among various enhancement algorithms, Retinex-based algorithms can efficiently enhance details and have been widely adopted. Since Retinex-based algorithms regard illumination removal as a default preference and fail to limit the range of reflectance, the naturalness of non-uniform illumination images cannot be effectively preserved. However, naturalness is essential for image enhancement to achieve pleasing perceptual quality. In order to preserve naturalness while enhancing details, we propose an enhancement algorithm for non-uniform illumination images. In general, this paper makes the following three major contributions. First, a lightness-order-error measure is proposed to access naturalness preservation objectively. Second, a bright-pass filter is proposed to decompose an image into reflectance and illumination, which, respectively, determine the details and the naturalness of the image. Third, we propose a bi-log transformation, which is utilized to map the illumination to make a balance between details and naturalness. Experimental results demonstrate that the proposed algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images.

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Citations
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Proceedings ArticleDOI

Low-light Image Enhancement Using Chain-consistent Adversarial Networks

TL;DR: In this paper , a semi-supervised method for low light image enhancement, using a chain of cycle consistent generators, was proposed, which is computationally efficient and does not require paired training data.
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A Novel Fusion Method for Low Brightness Enhancement Derivatives

TL;DR: Experiments demonstrate that the proposed algorithm can not only reveal the efficiency of the brightness and detail enhancement, but also can show its superiority over several state-of-the-art processes in terms of overall visual information enhancement.
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Bridge the Vision Gap from Field to Command: A Deep Learning Network Enhancing Illumination and Details.

TL;DR: NEID as discussed by the authors proposes a two-stream framework to tune up the brightness and enhance the details simultaneously without introducing many computational costs, which can aggregate composite features oriented to multiple tasks based on channel attention mechanism.
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A Retinex-based variational model for noise suppression and nonuniform illumination correction in corneal confocal microscopy images

TL;DR: Wang et al. as mentioned in this paper proposed a variational Retinex model for the inhomogeneity correction and noise removal of Corneal confocal microscopy (CCM) images.
Proceedings ArticleDOI

Skin Textural Generation via Blue-noise Gabor Filtering based Generative Adversarial Network

TL;DR: A novel Blue-Noise Gabor Module to produce a spatial-variant noisy image and a proposed two-branch framework combined facial identity enhancing with textures details generation to jointly produce a high-quality facial image.
References
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Journal ArticleDOI

Lightness and Retinex Theory

TL;DR: The mathematics of a lightness scheme that generates lightness numbers, the biologic correlate of reflectance, independent of the flux from objects is described.
Journal ArticleDOI

A multiscale retinex for bridging the gap between color images and the human observation of scenes

TL;DR: This paper extends a previously designed single-scale center/surround retinex to a multiscale version that achieves simultaneous dynamic range compression/color consistency/lightness rendition and defines a method of color restoration that corrects for this deficiency at the cost of a modest dilution in color consistency.
Book

Handbook of Image and Video Processing

Alan C. Bovik
TL;DR: The Handbook of Image and Video Processing contains a comprehensive and highly accessible presentation of all essential mathematics, techniques, and algorithms for every type of image and video processing used by scientists and engineers.
Journal ArticleDOI

Properties and performance of a center/surround retinex

TL;DR: A practical implementation of the retinex is defined without particular concern for its validity as a model for human lightness and color perception, and the trade-off between rendition and dynamic range compression that is governed by the surround space constant is described.
Journal ArticleDOI

Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement

TL;DR: A system level realization of CLAHE is proposed, which is suitable for VLSI or FPGA implementation and the goal for this realization is to minimize the latency without sacrificing precision.
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