A survey on image enhancement for Low-light images
In real scenes, due to the problems of low light and unsuitable views, the images often
exhibit a variety of degradations, such as low contrast, color distortion, and noise. These …
exhibit a variety of degradations, such as low contrast, color distortion, and noise. These …
A review of histogram equalization techniques in image enhancement application
WA Mustafa, MMM Abdul Kader - Journal of Physics: Conference …, 2018 - iopscience.iop.org
Image enhancement can be considered as one of the fundamental processes in image
analysis. The goal of contrast enhancement is to improve the quality of an image to become …
analysis. The goal of contrast enhancement is to improve the quality of an image to become …
LLNet: A deep autoencoder approach to natural low-light image enhancement
In surveillance, monitoring and tactical reconnaissance, gathering visual information from a
dynamic environment and accurately processing such data are essential to making informed …
dynamic environment and accurately processing such data are essential to making informed …
Feature split–merge–enhancement network for remote sensing object detection
Recently, multicategory object detection in high-resolution remote sensing images is still a
challenge. First, objects with significant scale differences exist in one scene simultaneously …
challenge. First, objects with significant scale differences exist in one scene simultaneously …
Automatic contrast-limited adaptive histogram equalization with dual gamma correction
We propose automatic contrast-limited adaptive histogram equalization (CLAHE) for image
contrast enhancement. We automatically set the clip point for CLAHE based on textureness …
contrast enhancement. We automatically set the clip point for CLAHE based on textureness …
[HTML][HTML] Robustness of machine learning to color, size change, normalization, and image enhancement on micrograph datasets with large sample differences
X Pei, Y hong Zhao, L Chen, Q Guo, Z Duan, Y Pan… - Materials & Design, 2023 - Elsevier
Appropriate image preprocessing could improve machine learning performance, but the
robustness of machine learning to preprocessing methods in micrograph datasets with …
robustness of machine learning to preprocessing methods in micrograph datasets with …
A low-light image enhancement method for both denoising and contrast enlarging
In this paper, a novel united low-light image enhancement framework for both contrast
enhancement and denoising is proposed. First, the low-light image is segmented into …
enhancement and denoising is proposed. First, the low-light image is segmented into …
Optimizing the topology of convolutional neural network (CNN) and artificial neural network (ANN) for brain tumor diagnosis (BTD) through MRIs
The use of MRI analysis for BTD and tumor type detection has considerable importance
within the domain of machine vision. Numerous methodologies have been proposed to …
within the domain of machine vision. Numerous methodologies have been proposed to …
No-reference quality assessment of contrast-distorted images using contrast enhancement
J Yan, J Li, X Fu - arXiv preprint arXiv:1904.08879, 2019 - arxiv.org
No-reference image quality assessment (NR-IQA) aims to measure the image quality without
reference image. However, contrast distortion has been overlooked in the current research …
reference image. However, contrast distortion has been overlooked in the current research …
Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients
This paper describes a new method for contrast enhancement in images and image
sequences of low-light or unevenly illuminated scenes based on statistical modelling of …
sequences of low-light or unevenly illuminated scenes based on statistical modelling of …