Abstract
In this work, we introduce a new content-adaptive compression scheme, called image primitive coding, which exploits the input image for training a dictionary. The atoms composed of the learned dictionary are named as image primitives. The coding performance between the learned image primitives and the traditional DCT basis is compared, and demonstrates the potential of image primitive coding. Furthermore, a novel concept, entropy of primitives (EoP), is proposed for measuring image visual information. Some very interesting results about EoP are achieved and analyzed, which can be further studied for visual quality assessment.
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhang, J., Ma, S., Xiong, R., Zhao, D., Gao, W. (2012). Image Primitive Coding and Visual Quality Assessment. In: Lin, W., et al. Advances in Multimedia Information Processing – PCM 2012. PCM 2012. Lecture Notes in Computer Science, vol 7674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34778-8_63
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DOI: https://doi.org/10.1007/978-3-642-34778-8_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34777-1
Online ISBN: 978-3-642-34778-8
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