Open AccessHybrid WPT‐BDCT transform for high‐quality image compression
Author(s) -
Thakur Vikrant Singh,
Gupta Shubhrata,
Thakur Kavita
Publication year - 2017
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2016.0740
Subject(s) - computer science , compression (physics) , artificial intelligence , image compression , image quality , computer vision , image (mathematics) , pattern recognition (psychology) , image processing , materials science , composite material
The image compression performance of transform coders highly depends on the energy compaction (EC) capability of transforms. The popular transforms such as discrete cosine transform (DCT) and discrete wavelet transform (DWT) provide decent EC; however, their capability is not enough to deliver good quality image reconstruction for higher compression levels (CLs). In this study, the authors propose a new hybrid transform which is a fusion of wavelet packet transform (WPT) and block‐DCT (BDCT) transform to achieve high‐quality image compression. This new hybrid WPT‐BDCT transform is able to attain higher EC than the existing transforms. Further, the authors have found a new energy compaction index (ECI) to evaluate the energy compactness of the image transforms. The proposed hybrid transform has been extensively evaluated, based on proposed ECI parameter, the visual quality assessment of reconstructed images and with the standard image quality indexes peak‐signal‐to‐noise ratio and structural similarity index measure. It is reported that the proposed hybrid transform provides higher EC and outperforms the transforms namely DCT, DWT, WPT, multi‐wavelet transform and existing hybrid transforms for all the CLs.