IMAGE NOISE REMOVAL USING ADAPTIVE SWITCHING MEDIAN FILTER BASED ON EXTREME LEARNING MACHINE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

KHORASHADIZADEH SEYYED MAJID; LATIF ALIMOHAMMAD

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2016 | Volume:- | Issue:1 (SERIAL 27) Page(s): 15-25

Download Full-Text

Persian Verion

View:

879

Download:

Cites:

Information Journal Paper

Title

IMAGE NOISE REMOVAL USING ADAPTIVE SWITCHING MEDIAN FILTER BASED ON EXTREME LEARNING MACHINE

Author(s)

KHORASHADIZADEH SEYYED MAJID | LATIF ALIMOHAMMAD | Issue Writer Certificate

Keywords

NOISE REMOVALQ1

EXTREME LEARNING MACHINEQ2

ADAPTIVE MEDIAN FILTERQ2

SALT AND PEPPER NOISEQ2

SWITCHING FILTERQ2

Abstract

In this paper an efficient approach based on the EXTREME LEARNING MACHINE, for identifying and modifying image pixels which are contaminated by salt pepper is presented. The proposed algorithm uses an EXTREME LEARNING MACHINE to identify noisy pixels in digital image. Decision of the ELM is based on six inputs including: central pixel, ROAD factor and four measurements of SD-ROM filter. In the next phase, best values for each of the noisy pixels is estimated using an ADAPTIVE MEDIAN FILTER. The results of the performance evaluation of classification, represents the high capability of input features in discriminating noisy pixels from noise-free pixels. To evaluate the performance, the output image of the proposed algorithm is compared with the output of several other common filter in terms of PSNR ratio. The numerical results obtained from the tests indicate efficiency of proposed filter in terms of qualitative and quantitative criteria.

Cites

No record.

References

No record.

Cite

APA: Copy

KHORASHADIZADEH, SEYYED MAJID, & LATIF, ALIMOHAMMAD. (2016). IMAGE NOISE REMOVAL USING ADAPTIVE SWITCHING MEDIAN FILTER BASED ON EXTREME LEARNING MACHINE. SIGNAL AND DATA PROCESSING, -(1 (SERIAL 27)), 15-25. SID. https://sid.ir/paper/160728/en

Vancouver: Copy

KHORASHADIZADEH SEYYED MAJID, LATIF ALIMOHAMMAD. IMAGE NOISE REMOVAL USING ADAPTIVE SWITCHING MEDIAN FILTER BASED ON EXTREME LEARNING MACHINE. SIGNAL AND DATA PROCESSING[Internet]. 2016;-(1 (SERIAL 27)):15-25. Available from: https://sid.ir/paper/160728/en

IEEE: Copy

SEYYED MAJID KHORASHADIZADEH, and ALIMOHAMMAD LATIF, “IMAGE NOISE REMOVAL USING ADAPTIVE SWITCHING MEDIAN FILTER BASED ON EXTREME LEARNING MACHINE,” SIGNAL AND DATA PROCESSING, vol. -, no. 1 (SERIAL 27), pp. 15–25, 2016, [Online]. Available: https://sid.ir/paper/160728/en

Related Journal Papers