Image Quality Assessment for Different Wavelet Compression Techniques in a Visual Communication Framework
Author(s) -
Nuha A. S. Alwan,
Zahir M. Hussain
Publication year - 2013
Publication title -
modelling and simulation in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 20
eISSN - 1687-5591
pISSN - 1687-5605
DOI - 10.1155/2013/818696
Subject(s) - artificial intelligence , wavelet , image compression , mean squared error , additive white gaussian noise , image quality , peak signal to noise ratio , computer vision , data compression , computer science , pattern recognition (psychology) , mathematics , image processing , channel (broadcasting) , statistics , image (mathematics) , telecommunications
Images with subband coding and threshold wavelet compression are transmitted over a Rayleigh communication channel with additive white Gaussian noise (AWGN), after quantization and 16-QAM modulation. A comparison is made between these two types of compression using both mean square error (MSE) and structural similarity (SSIM) image quality assessment (IQA) criteria applied to the reconstructed image at the receiver. The two methods yielded comparable SSIM but different MSE measures. In this work, we justify our results which support previous findings in the literature that the MSE between two images is not indicative of structural similarity or the visibility of errors. It is found that it is difficult to reduce the pointwise errors in subband-compressed images (higher MSE). However, the compressed images provide comparable SSIM or perceived quality for both types of compression provided that the retained energy after compression is the same
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