A New Classification Performance Aware Multi sensor, Multi resolution Satellite image compression Technique

1
Maryam Sahami Gilani
Maryam Sahami Gilani
2
Ch. Ramesh
Ch. Ramesh
3
Dr. N.B. Venkateswarlu
Dr. N.B. Venkateswarlu
4
Dr. J.V.R. Murthy
Dr. J.V.R. Murthy
1 Islamic Azad University, Takestan, Iran
2 Aditya Institute of Technology and Management/JNTUK

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Effective utilization of bandwidth and storage space is important in imaging applications including remote sensing. Remote sensing applications use multi-sensory, multi-band, multi resolution images. Usually, remote sensing applications uses image classification results for their analysis and decision making. In this paper we propose a new JPEG based image compression algorithm based on zooming-shrinking technique. Proposed algorithm performance is evaluated in relation to standard JPEG algorithm. In order to envisage the effect of compression on classification performance, Maximum Likelihood, Mahalanobis and Minimum distance classifiers performance is evaluated with original image data, standard JPEG compressed data and the compressed image data with the proposed method. Experiments are carried out with multi-band images with various resolutions. Our experiments supports that the classification accuracies of compressed images are at par with original image data.

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No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

Maryam Sahami Gilani. 1970. \u201cA New Classification Performance Aware Multi sensor, Multi resolution Satellite image compression Technique\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F7): .

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GJCST Volume 13 Issue F7
Pg. 13- 23
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Crossref Journal DOI 10.17406/gjcst

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Effective utilization of bandwidth and storage space is important in imaging applications including remote sensing. Remote sensing applications use multi-sensory, multi-band, multi resolution images. Usually, remote sensing applications uses image classification results for their analysis and decision making. In this paper we propose a new JPEG based image compression algorithm based on zooming-shrinking technique. Proposed algorithm performance is evaluated in relation to standard JPEG algorithm. In order to envisage the effect of compression on classification performance, Maximum Likelihood, Mahalanobis and Minimum distance classifiers performance is evaluated with original image data, standard JPEG compressed data and the compressed image data with the proposed method. Experiments are carried out with multi-band images with various resolutions. Our experiments supports that the classification accuracies of compressed images are at par with original image data.

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A New Classification Performance Aware Multi sensor, Multi resolution Satellite image compression Technique

Ch. Ramesh
Ch. Ramesh Aditya Institute of Technology and Management/JNTUK
Dr. N.B. Venkateswarlu
Dr. N.B. Venkateswarlu
Dr. J.V.R. Murthy
Dr. J.V.R. Murthy

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