Compression of High-Spatial-Resolution Images Based on Estimating the Detail Sub-bands in the Wavelet Domain

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.

GRAILU HADI

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

Journal Paper

Paper Information

Journal: MACHINE VISION AND IMAGE PROCESSING Year:2018 | Volume:5 | Issue:1 Page(s): 53-71

Download Full-Text

Persian Verion

View:

342

Download:

Cites:

Information Journal Paper

Title

Compression of High-Spatial-Resolution Images Based on Estimating the Detail Sub-bands in the Wavelet Domain

Author(s)

GRAILU HADI | Issue Writer Certificate

Keywords

Image Compression

Image Enlargement

Sub-band Estimation

Textual Image

Face Image

Compression

Recognition Performance

Abstract

Proper spatial resolution has great importance in many image types since it conveys significant details. Performance of feature extraction methods, in some image types such as textual, facial, and fingerprint ones, highly depend on the image quality. Spatial resolution is one of important factors affecting the image quality; but, high spatial resolution increases the storage memory of the corresponding images, showing the importance of Compression/fa?page=1&sort=1&ftyp=all&fgrp=all&fyrs=all" target="_blank">Image Compression methods. In the proposed Compression/fa?page=1&sort=1&ftyp=all&fgrp=all&fyrs=all" target="_blank">Image Compression approach of this paper, dimension of the input image is first decreased based on the wavelet transform and then is compressed using any desired Compression/fa?page=1&sort=1&ftyp=all&fgrp=all&fyrs=all" target="_blank">Image Compression method. In the deCompression stage, first, the dimensionally reduced image is reconstructed and then, the initial dimension is restored by our proposed technique of estimating the detail sub-bands in the wavelet domain. In the evaluation stage, we chose two image types of textual and facial as two case studies having band-pass and low-pass spectrums respectively. We evaluated the Compression and Recognition Performance of proposed approach by combining it with any of conventional Compression methods of JPEG, JPEG2000 and SPIHT. Simulation results showed the noticeable effect of the proposed approach on reducing the storage memory and simultaneously, preserving o the Compression/Recognition Performance.

Cites

No record.

References

No record.

Cite

APA: Copy

GRAILU, HADI. (2018). Compression of High-Spatial-Resolution Images Based on Estimating the Detail Sub-bands in the Wavelet Domain. MACHINE VISION AND IMAGE PROCESSING, 5(1 ), 53-71. SID. https://sid.ir/paper/360071/en

Vancouver: Copy

GRAILU HADI. Compression of High-Spatial-Resolution Images Based on Estimating the Detail Sub-bands in the Wavelet Domain. MACHINE VISION AND IMAGE PROCESSING[Internet]. 2018;5(1 ):53-71. Available from: https://sid.ir/paper/360071/en

IEEE: Copy

HADI GRAILU, “Compression of High-Spatial-Resolution Images Based on Estimating the Detail Sub-bands in the Wavelet Domain,” MACHINE VISION AND IMAGE PROCESSING, vol. 5, no. 1 , pp. 53–71, 2018, [Online]. Available: https://sid.ir/paper/360071/en

Related Journal Papers