Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/5697
Title: Combined DCT-Haar transforms for image compression
Authors: Dagher, Issam 
Saliba, Mireille
Farah, Rachelle
Affiliations: Faculty of Engineering 
Keywords: Discrete Cosine Transformation
Haar
Hybrid
Image compression
Wavelet
Issue Date: 2018-12-01
Publisher: Wiley Online Library
Part of: International Journal of Imaging Systems and Technology
Volume: 28
Issue: 4
Start page: 274
End page: 294
Abstract: 
Discrete Cosine Transform and Haar wavelet transform are very important transforms in image compression. The objective of this paper is to combine the advantages of these 2 transforms into one transform in order to get better peak-signal-to-noise-ratio (PSNR) and keeping good compression ratio. Our first approach was to apply separately on each 8x8 block the Haar and the DCT transforms. A signaling bit along the transform which gave better PSNR are quantized and transmitted. Our second approach was to construct a new hybrid transform which is a combination of these 2 transforms. We mixed both DCT and Haar transforms into one transform. Results show that our approach outperforms the existing DCT and Haar methods giving a higher PSNR than DCT for the same compression ratio, and permitting better edge recovery than the Haar transform.
URI: https://scholarhub.balamand.edu.lb/handle/uob/5697
ISSN: 08999457
DOI: 10.1002/ima.22286
Ezproxy URL: Link to full text
Type: Journal Article
Appears in Collections:Department of Computer Engineering

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