Title: Improvement of image compression approach using dynamic quantisation based on HVS

Authors: Mourad Rahali; Habiba Loukil; Med Salim Bouhlel

Addresses: Sciences and Technologies of Image and Telecommunications, High Institute of Biotechnology, University of Sfax, Street of Sokra, 3000, Tunisia; National Engineering School of Gabes, University of Gabes, Street of Omar Ibn El Khattab, Zrig Eddakhlania, 6072, Tunisia ' Sciences and Technologies of Image and Telecommunications High Institute of Biotechnology, University of Sfax, Street of Sokra, 3000, Tunisia ' Sciences and Technologies of Image and Telecommunications High Institute of Biotechnology, University of Sfax, Street of Sokra, 3000, Tunisia

Abstract: Digital-image compression can reduce the overall volume of the image by keeping the original image with the minimum degradation in the level of the reconstructed image quality; in other words, here, we speak about compression with loss. This work comes up with an improvement in an image compression method using the discrete wavelet transform (DWT) and neural networks. To improve this technique, we have added a new phase based on the Human Visual System (HVS) and the Weber-Fechner law to dynamically quantify the image signal. Such a new phase can improve the quality of compression by dynamically quantifying each pixel value of the original image compared to the values of the neighbour pixels according to a luminance detection threshold. This threshold is known as Weber constant.

Keywords: image compression; human visual system; dynamic quantisation; Weber-Fechner law; Weber constant.

DOI: 10.1504/IJSISE.2019.100648

International Journal of Signal and Imaging Systems Engineering, 2019 Vol.11 No.5, pp.259 - 269

Received: 12 Dec 2017
Accepted: 04 Jul 2018
Published online: 06 Jul 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article