Additive Gaussian noise removal based on generative adversarial network model and semi-soft thresholding approach
A Khmag - Multimedia Tools and Applications, 2023 - Springer
In digital image analysis and processing field of study, noise reduction and suppression
have been stated as a common query. However, it is mostly essential issue to demesne the …
have been stated as a common query. However, it is mostly essential issue to demesne the …
Computer vision techniques for growth prediction: A prisma-based systematic literature review
Growth prediction technology is not only a practical application but also a crucial approach
that strengthens the safety of image processing techniques. By supplementing the growth …
that strengthens the safety of image processing techniques. By supplementing the growth …
Smoke removal technique of industrial scene images based on second-generation wavelets and dark channel prior model
A Khmag - Soft Computing, 2023 - Springer
The world has seen a ground-breaking development in the utilization of digital images and
their applications in modern society. Practically, digital images which are captured in hazy …
their applications in modern society. Practically, digital images which are captured in hazy …
Face recognition system based on four state hidden Markov model
Computational complexity is a matter of great concern in real time face recognition systems.
In this paper, four state hidden Markov model for face recognition has been presented …
In this paper, four state hidden Markov model for face recognition has been presented …
Image denoising method integrating ridgelet transform and improved wavelet threshold
B Li, Y Cong, H Mo - PLoS One, 2024 - journals.plos.org
In the field of image processing, common noise types include Gaussian noise, salt and
pepper noise, speckle noise, uniform noise and pulse noise. Different types of noise require …
pepper noise, speckle noise, uniform noise and pulse noise. Different types of noise require …
Additive white gaussian noise level estimation for natural images using linear scale-space features
Noise in images is often modelled with additive white Gaussian noise (AWGN). An accurate
estimation of noise level without any prior knowledge of noisy input image leads to effective …
estimation of noise level without any prior knowledge of noisy input image leads to effective …
ADMM optimizer for integrating wavelet-patch and group-based sparse representation for image inpainting
AS Arya, A Saha, S Mukhopadhyay - The Visual Computer, 2024 - Springer
Recovery or filling in of missing pixels in damaged images is a challenging problem known
as image inpainting. Many currently used techniques still suffer from artifacts and other …
as image inpainting. Many currently used techniques still suffer from artifacts and other …
Digital image noise removal based on collaborative filtering approach and singular value decomposition
A Khmag - Multimedia Tools and Applications, 2022 - Springer
Image denoising is a crucial step in order to improve digital image quality. Furthermore, the
digital image in sparse format especially in low-rank structure has been utilized in several …
digital image in sparse format especially in low-rank structure has been utilized in several …
Gradient and multi scale feature inspired deep blind gaussian denoiser
In this paper, a novel deep blind Gaussian denoising network is proposed utilizing the
concepts of gradient information, multi-scale feature information and feature denoising for …
concepts of gradient information, multi-scale feature information and feature denoising for …
Rock image segmentation of improved semi-supervised SVM–FCM algorithm based on chaos
H Liang, J Zou - Circuits, Systems, and Signal Processing, 2020 - Springer
In the process of petroleum resource exploitation, porosity is the key parameter to evaluate
reservoir fluid fluidity. Rock image segmentation is a challenging task due to the complex …
reservoir fluid fluidity. Rock image segmentation is a challenging task due to the complex …