Impulsive noise filtering based on noise detection in corrupted digital color images

Kwanghoon Sohn, Kyu Cheol Lee, Jungeun Lim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper is an enhancement to our earlier research with grey-scale images. In this paper, we propose two new detection-estimation based image filtering algorithms that effectively remove corrupted pixels with impulsive noise in digital color images. The existing methods for enhancing corrupted color images typically possess inherent problems in computation time and smoothing out edges because all pixels are filtered. Our proposed algorithms first classify corrupted pixels in each channel or in each pixel. Because marginal or vector median filtering is only performed for the classified pixels, the process is computationally efficient, and edges are preserved well. In addition, because there is no appropriate criterion to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor for comparing the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than existing methods, in both objective and subjective evaluations.

Original languageEnglish
Pages (from-to)643-654
Number of pages12
JournalCircuits, Systems, and Signal Processing
Volume20
Issue number6
DOIs
Publication statusPublished - 2001 Jan 1

Fingerprint

Noise Filtering
Impulsive Noise
Impulse noise
Color Image
Digital Image
Pixel
Pixels
Color
Detector
Detectors
Efficiency Factor
Image Filtering
Subjective Evaluation
Smoothing
Filtering
Enhancement
Classify
Evaluate
Simulation

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Applied Mathematics

Cite this

@article{c43faf2fc3ce4111bd1675631343932b,
title = "Impulsive noise filtering based on noise detection in corrupted digital color images",
abstract = "This paper is an enhancement to our earlier research with grey-scale images. In this paper, we propose two new detection-estimation based image filtering algorithms that effectively remove corrupted pixels with impulsive noise in digital color images. The existing methods for enhancing corrupted color images typically possess inherent problems in computation time and smoothing out edges because all pixels are filtered. Our proposed algorithms first classify corrupted pixels in each channel or in each pixel. Because marginal or vector median filtering is only performed for the classified pixels, the process is computationally efficient, and edges are preserved well. In addition, because there is no appropriate criterion to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor for comparing the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than existing methods, in both objective and subjective evaluations.",
author = "Kwanghoon Sohn and Lee, {Kyu Cheol} and Jungeun Lim",
year = "2001",
month = "1",
day = "1",
doi = "10.1007/BF01270934",
language = "English",
volume = "20",
pages = "643--654",
journal = "Circuits, Systems, and Signal Processing",
issn = "0278-081X",
publisher = "Birkhause Boston",
number = "6",

}

Impulsive noise filtering based on noise detection in corrupted digital color images. / Sohn, Kwanghoon; Lee, Kyu Cheol; Lim, Jungeun.

In: Circuits, Systems, and Signal Processing, Vol. 20, No. 6, 01.01.2001, p. 643-654.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Impulsive noise filtering based on noise detection in corrupted digital color images

AU - Sohn, Kwanghoon

AU - Lee, Kyu Cheol

AU - Lim, Jungeun

PY - 2001/1/1

Y1 - 2001/1/1

N2 - This paper is an enhancement to our earlier research with grey-scale images. In this paper, we propose two new detection-estimation based image filtering algorithms that effectively remove corrupted pixels with impulsive noise in digital color images. The existing methods for enhancing corrupted color images typically possess inherent problems in computation time and smoothing out edges because all pixels are filtered. Our proposed algorithms first classify corrupted pixels in each channel or in each pixel. Because marginal or vector median filtering is only performed for the classified pixels, the process is computationally efficient, and edges are preserved well. In addition, because there is no appropriate criterion to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor for comparing the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than existing methods, in both objective and subjective evaluations.

AB - This paper is an enhancement to our earlier research with grey-scale images. In this paper, we propose two new detection-estimation based image filtering algorithms that effectively remove corrupted pixels with impulsive noise in digital color images. The existing methods for enhancing corrupted color images typically possess inherent problems in computation time and smoothing out edges because all pixels are filtered. Our proposed algorithms first classify corrupted pixels in each channel or in each pixel. Because marginal or vector median filtering is only performed for the classified pixels, the process is computationally efficient, and edges are preserved well. In addition, because there is no appropriate criterion to evaluate the performance of impulsive noise detectors for color images, the objective comparison of noise detectors is difficult. Thus, we introduce a new efficiency factor for comparing the performance of noise detectors in digital color images. Simulation results show that the proposed algorithms perform better than existing methods, in both objective and subjective evaluations.

UR - http://www.scopus.com/inward/record.url?scp=0035518176&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035518176&partnerID=8YFLogxK

U2 - 10.1007/BF01270934

DO - 10.1007/BF01270934

M3 - Article

VL - 20

SP - 643

EP - 654

JO - Circuits, Systems, and Signal Processing

JF - Circuits, Systems, and Signal Processing

SN - 0278-081X

IS - 6

ER -