Alpha Trimmed Mean based JPEG Compression for an Objective Image Quality Enhancement of Noisy and Noise less Images

Vanitha Kakollu; P. Chandrasekhar Reddy

Alpha Trimmed Mean based JPEG Compression for an Objective Image Quality Enhancement of Noisy and Noise less Images

Vanitha Kakollu * §

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P. Chandrasekhar Reddy

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§ GITAM INSTITUTE OF SCIENCE

Alpha Trimmed Mean based JPEG Compression for an Objective Image Quality Enhancement of Noisy and Noise less Images

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Abstract

We can see that over the past few years, the number of people using the internet and the amount of information transmitted over the internet has grown to such a wide range. One of the best ways to reduce the image size is via image compression. In the compression of the still image, JPEG is better when it comes to bandwidth conservation. In this paper, we discussed an innovative JPEG compression algorithm with alpha-trimmed means based clustering. The proposed algorithm is expected to produce better results regarding MSE, PSNR and the number of bits transmitted when compared to the standard algorithms. The proposed JPEG algorithm enhances the speed and reduces the number of encoded bits, thereby reducing the amount of memory required. The reassembled image after decompression is as similar as the input image.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Vanitha Kakollu, P. Chandrasekhar Reddy. 2018. "Alpha Trimmed Mean based JPEG Compression for an Objective Image Quality Enhancement of Noisy and Noise less Images". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 17 (GJCST Volume 17 Issue F3).

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GJCST Volume 17 Issue F3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

B.4.2

I.4.1

Submission ReceivedDecember 7, 2016
Peer Review Double Blind
Handling Editor
Accepted January 4, 2017
Published January 15, 2017

Version of record

v1.2

Issue date

January 17, 2018

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Vanitha Kakollu, G. Narasimha, P. Chandrasekhar Reddy (PhD/Dr. count: 0)

View Count (all-time): 421

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Publish Date: 2017 01, Sun

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Total Views: 2.7K

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