2022
DOI: 10.11591/ijeecs.v28.i2.pp777-786
|View full text |Cite
|
Sign up to set email alerts
|

Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter

Abstract: Acquisition of images from electronic devices or Transmission of the image through any medium will cause an additional commotion. This study aims to investigate a framework for eliminating impulse noise from grayscale and medical images by utilizing linear regression and a mean filter. Linear regression is a supervised machine learning algorithm that computes the value of a dependent variable based on an independent variable. The value of the recuperating pixel is measured using a curve-fitting, direction-base… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 28 publications
0
2
0
Order By: Relevance
“…The average bitrate is increased by a huge percentage with the presence of noise in images [14]. Hence, denoising techniques [15], [16] are required to combine with in-loop filters of coding standards for enhancing coding efficiency. Therefore, the proposed method of this paper is an improved fast-guided filter next to the deblocking filter in the VVC.…”
Section: Figure 1 In-loop Filters In Vvcmentioning
confidence: 99%
“…The average bitrate is increased by a huge percentage with the presence of noise in images [14]. Hence, denoising techniques [15], [16] are required to combine with in-loop filters of coding standards for enhancing coding efficiency. Therefore, the proposed method of this paper is an improved fast-guided filter next to the deblocking filter in the VVC.…”
Section: Figure 1 In-loop Filters In Vvcmentioning
confidence: 99%
“…A machine vision application utilizing an image processing method established a new method of rice seed classification that applies hashing techniques for preprocessing image prediction [17]. The linear regression algorithm which calculates the value of a dependent variable, establishes an independent variable [18]. The hybrid bat algorithm and genetic algorithm model are employed on noisy medical images to reduce noise, and their performances have been determined by arithmetical analyses such as peak signal-to-noise ratio (PSNR) [19].…”
Section: Introductionmentioning
confidence: 99%