L2 norm optimization of tone mapping for two layer lossless coding of HDR images

Iwahashi, Masahiro; Yoshida, Taichi; Kiya, Hitoshi

doi:10.1109/apsipa.2014.7041614

Cited by 2 publications

(5 citation statements)

References 20 publications

(16 reference statements)

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“…To cope with this problem, we previously introduced the reversible logarithmic mapping (Rev) to reduce the bit depth of the residual image [19]. However, in this previous report, we only presented experimental results without any theoretical endorsement.…”

Section: Problem Settingmentioning

confidence: 85%

“…The reversible integer mapping Int from the real value x H to the integer value x I was introduced in [19]. It is defined as…”

Section: Reversible Integer Mappingmentioning

confidence: 99%

“…In this paper, we improve on our previous conference papers [19,21] and add some theoretical analysis. First, we show that a simple extension of the reversible logarithmic mapping (Rev) to the RGBE format degrades the visual quality of the decoded LDR images.…”

Section: Introductionmentioning

confidence: 99%

“…Although the baseline method is straightforward and easy to implement, the coding efficiency in the enhancement layer is not satisfactory. To cope with this problem, we introduced a reversible logarithmic mapping and reduced the dynamic range of the HDR images [19,21]. This approach was shown to be effective for compressing data in the enhancement layer.…”

Section: Introductionmentioning

confidence: 99%

“…First, we discuss a baseline method [19] that was simply extended to lossless scalable coding from a nonscalable HDR image coding method [20]. Although the baseline method is straightforward and easy to implement, the coding efficiency in the enhancement layer is not satisfactory.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Bit-depth scalable lossless coding for high dynamic range images

Iwahashi

Yoshida

Mokhtar

et al. 2015

EURASIP J. Adv. Signal Process.

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In this paper, we propose a bit-depth scalable lossless coding method for high dynamic range (HDR) images based on a reversible logarithmic mapping. HDR images are generally expressed as floating-point data, such as in the OpenEXR or RGBE formats. Our bit-depth scalable coding approach outputs base layer data and enhancement layer data. It can reconstruct the low dynamic range (LDR) image from the base layer data and reconstructs the HDR image by adding the enhancement layer data. Most previous two-layer methods have focused on the lossy coding of HDR images. Unfortunately, the extension of previous lossy methods to lossless coding does not significantly compress the enhancement layer data. This is because the bit depth becomes very large, especially for HDR images in floating-point data format. To tackle this problem, we apply a reversible logarithmic mapping to the input HDR data. Moreover, we introduce a format conversion to avoid any degradation in the quality of the reconstructed LDR image. The proposed method is effective for both OpenEXR and RGBE formats. Through a series of experiments, we confirm that the proposed method decreases the volume of compressed data while maintaining the visual quality of the reconstructed LDR images.

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Section: Problem Settingmentioning

confidence: 85%

“…The reversible integer mapping Int from the real value x H to the integer value x I was introduced in [19]. It is defined as…”

Section: Reversible Integer Mappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%