Image Primitive Coding and Visual Quality Assessment
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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.
Keywordsimage coding image primitive visual information visual quality assessment (VQA)
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- 1.Pennebaker, W.B., Mitchell, J.L.: JPEG still image data compression standard. Springer, New York (1993)Google Scholar
- 2.Taubman, D.S., Marcellin, M.W.: JPEG2000: Image compression fundamentals, standards and practice. Kluwer Academic Publishers, Norwell (2001)Google Scholar
- 4.Elad, M.: Sparse and redundant representations–From theory to applications in signal and image processing. Springer (2010)Google Scholar
- 6.Zepeda, J., Guillemot, C., Kijak, E.: Image Compression using the Iteration-Tuned and Aligned Dictionary. In: 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 793–796. IEEE Press (2011)Google Scholar