Paper
14 February 2008 On the performance of human visual system based image quality assessment metric using wavelet domain
Author Affiliations +
Proceedings Volume 6806, Human Vision and Electronic Imaging XIII; 680610 (2008) https://doi.org/10.1117/12.766536
Event: Electronic Imaging, 2008, San Jose, California, United States
Abstract
Most of the efficient objective image or video quality metrics are based on properties and models of the Human Visual System (HVS). This paper is dealing with two major drawbacks related to HVS properties used in such metrics applied in the DWT domain : subband decomposition and masking effect. The multi-channel behavior of the HVS can be emulated applying a perceptual subband decomposition. Ideally, this can be performed in the Fourier domain but it requires too much computation cost for many applications. Spatial transform such as DWT is a good alternative to reduce computation effort but the correspondence between the perceptual subbands and the usual wavelet ones is not straightforward. Advantages and limitations of the DWT are discussed, and compared with models based on a DFT. Visual masking is a sensitive issue. Several models exist in literature. Simplest models can only predict visibility threshold for very simple cue while for natural images one should consider more complex approaches such as entropy masking. The main issue relies on finding a revealing measure of the surround influences and an adaptation: should we use the spatial activity, the entropy, the type of texture, etc.? In this paper, different visual masking models using DWT are discussed and compared.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Ninassi, O. Le Meur, P. Le Callet, and D. Barba "On the performance of human visual system based image quality assessment metric using wavelet domain", Proc. SPIE 6806, Human Vision and Electronic Imaging XIII, 680610 (14 February 2008); https://doi.org/10.1117/12.766536
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CITATIONS
Cited by 28 scholarly publications and 6 patents.
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KEYWORDS
Image quality

Discrete wavelet transforms

Visual system

Wavelets

Electronic imaging

Fourier transforms

Information technology

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