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Author:

Wang, Jin (Wang, Jin.) | Li, Shenda (Li, Shenda.) | Zhu, Qing (Zhu, Qing.)

Indexed by:

EI Scopus

Abstract:

With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, this method does not make full use of HVS, causing waste of bits on imperceptible regions to human eyes. In this paper, a visual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. Moreover, our proposed method offers the JPEG compatibility at the same time. © 2020 The Author(s) published by Cambridge University Press in association with Asia Pacific Signal and Information Processing Association.

Keyword:

Visualization Image compression Codes (symbols) Image coding

Author Community:

  • [ 1 ] [Wang, Jin]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Wang, Jin]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing, China
  • [ 3 ] [Li, Shenda]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Zhu, Qing]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

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Source :

APSIPA Transactions on Signal and Information Processing

Year: 2020

Volume: 9

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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