JOURNAL ARTICLE

<title>New image compression artifact measure using wavelets</title>

Yung‐Kai LaiC.‐C. Jay KuoJin Li

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3024 Pages: 897-908   Publisher: SPIE

Abstract

Traditional objective metrics for the quality measure of coded images such as the mean squared error (MSE) and the peak signal-to-noise ratio do not correlate with the subjective human visual experiences well, since they do not take human perception into account. Quantification of artifacts resulted from lossy image compression techniques is studied based on a human visual systems (HVS) model and the time-space localization property of the wavelet transform is exploited to simulate HVS in this research. As a result of our research, a new image quality measure by using the wavelet basis function is proposed. This new metric works for a wide variety of compression artifacts. Experimental results are given to demonstrate that it is more consistent with human subjective ranking.

Keywords:
Human visual system model Artificial intelligence Wavelet Image compression Artifact (error) Lossy compression Computer science Measure (data warehouse) Computer vision Metric (unit) Image quality Pattern recognition (psychology) Wavelet transform Noise (video) Data compression Property (philosophy) Ranking (information retrieval) Mathematics Image (mathematics) Image processing Data mining Engineering

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2
Cited By
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FWCI (Field Weighted Citation Impact)
0
Refs
0.15
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Is in top 1%
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Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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