Histogram modification in adaptive bi-histogram equalization for contrast enhancement on digital images
In this paper, a novel histogram modification-based bi histogram equalization (HE) approach
for contrast enhancement on digital images is presented. At first, a power-logarithm …
for contrast enhancement on digital images is presented. At first, a power-logarithm …
Image edge smoothing method for light-field displays based on joint design of optical structure and elemental images
X Yu, H Li, X Su, X Gao, X Sang, B Yan - Optics Express, 2023 - opg.optica.org
Image visual quality is of fundamental importance for three-dimensional (3D) light-field
displays. The pixels of a light-field display are enlarged after the imaging of the light-field …
displays. The pixels of a light-field display are enlarged after the imaging of the light-field …
Research challenges and future directions towards medical data processing
A Ampavathi - Computer Methods in Biomechanics and Biomedical …, 2022 - Taylor & Francis
Data in the healthcare industry and machine learning techniques is useful to analyse a huge
amount of data to identify the hidden patterns in the disease, to give personalised treatment …
amount of data to identify the hidden patterns in the disease, to give personalised treatment …
Dual-stream multi-path recursive residual network for JPEG image compression artifacts reduction
JPEG is the most widely used lossy image compression standard. When using JPEG with
high compression ratios, visual artifacts cannot be avoided. These artifacts not only degrade …
high compression ratios, visual artifacts cannot be avoided. These artifacts not only degrade …
Low-dose COVID-19 CT image denoising using batch normalization and convolution neural network
Computed tomography (CT) is used in medical applications to produce digital medical
imaging of the human body and is acquired by the reconstruction process, where X-rays are …
imaging of the human body and is acquired by the reconstruction process, where X-rays are …
Learning deep texture-structure decomposition for low-light image restoration and enhancement
A great many low-light image restoration methods have built their models according to
Retinex theory. However, most of these methods cannot well achieve image detail …
Retinex theory. However, most of these methods cannot well achieve image detail …
A new blind image denoising method based on asymmetric generative adversarial network
Image denoising is a classical topic in computer vision. In recent years, with the
development of deep learning, image denoising methods based on discriminative learning …
development of deep learning, image denoising methods based on discriminative learning …
Edge preserving range image smoothing using hybrid locally kernel-based weighted least square
In this paper, we propose the hybrid locally kernel-based weighted least square (HKLS)
method to reduce the noise of the range images captured from the Microsoft Kinect sensor …
method to reduce the noise of the range images captured from the Microsoft Kinect sensor …
Image Super-Resolution Using Sparse Representation And Novelty Noise Removal Super-Resolution
SH Ahmed, S Kurnaz… - 2020 4th International …, 2020 - ieeexplore.ieee.org
The reconstruction of a composite image with a super-resolution will produce a high-
resolution image from a low-resolution picture. Since the super-resolution problem is not …
resolution image from a low-resolution picture. Since the super-resolution problem is not …
Edge-aware filter based on adaptive patch variance weighted average
Edge-aware smoothing is an essential tool for computer vision, graphics and photography.
In this paper, we develop a new and efficient local weighted average filter for edge-aware …
In this paper, we develop a new and efficient local weighted average filter for edge-aware …