Subband encoding of high dynamic range imagery

Ward, Greg; Simmons, Maryann

doi:10.1145/1012551.1012566

Cited by 62 publications

(39 citation statements)

References 15 publications

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“…A few backward compatible algorithms [47,27,23] contain a tone-mapped (TM) stream which enables it to be played on legacy video players. The residual stream contains additional information to be used for reconstruction of HDR frames during decompression.…”

Section: Hdr Video Compression Algorithmsmentioning

confidence: 99%

“…Ward and Simmons (2004) [47] proposed a backward compatible algorithm to encode HDR images. The proposed algorithm extends the standard JPEG image format by tone mapping input HDR frames using the photographic TMO [37] and storing multiplicative HDR information, defined as the ratio between luminance of the HDR and the tone mapped frame: RI(x, y) =…”

Section: Ward and Simmons (Hdrjpeg)mentioning

confidence: 99%

“…Using the dual-loop encoding scheme, the TM stream is encoded and decoded to create a ratio stream similar to [47]. Subsequently, a bilateral filter is applied to the ratio frames to reduce noise artefacts.…”

Section: Lee and Kim (Rate)mentioning

confidence: 99%

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Objective and subjective evaluation of High Dynamic Range video compression

Mukherjee

Debattista

Bashford-Rogers

et al. 2016

Signal Processing: Image Communication

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Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. AbstractA number of High Dynamic Range (HDR) video compression algorithms proposed to date have either been developed in isolation or only-partially compared with each other. Previous evaluations were conducted using quality assessment error metrics, which for the most part were developed for qualitative assessment of Low Dynamic Range (LDR) videos. This paper presents a comprehensive objective and subjective evaluation conducted with six published HDR video compression algorithms. The objective evaluation was undertaken on a large set of 39 HDR video sequences using seven numerical error metrics namely: PSNR, logPSNR, puPSNR, puSSIM, Weber MSE, HDR-VDP and HDR-VQM. The subjective evaluation involved six short-listed sequences and two ranking-based subjective experiments with hidden reference at two different output bitrates with 32 participants each, who were tasked to rank distorted HDR video footage compared to an uncompressed version of the same footage. Results suggest a strong correlation between the objective and subjective evaluation. Also, non-backward compatible compression algorithms appear to perform better at lower output bit rates than backward compatible algorithms across the settings used in this evaluation.

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Section: Hdr Video Compression Algorithmsmentioning

confidence: 99%

Section: Ward and Simmons (Hdrjpeg)mentioning

confidence: 99%

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Objective and subjective evaluation of High Dynamic Range video compression

Mukherjee

Debattista

Bashford-Rogers

et al. 2016

Signal Processing: Image Communication

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“…However, realworld dynamic range is far greater than 256 intensity levels. Also humans can simultaneously perceive contrast ratio of more than 4 orders of magnitude, and adapt their sensitivity up and down another 6 orders [8].…”

Section: Introductionmentioning

confidence: 99%

“…[14][15][16]). We focus here on lossless image compressions as opposed to bit encodings for each pixel.…”

Section: Introductionmentioning

confidence: 99%

On performance of lossless compression for HDR image quantized in color space

Fang

2009

Signal Processing: Image Communication

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High Dynamic Range Imaging

Mantiuk

Seidel

2015

Wiley Encyclopedia of Electrical and Electronics Engineering

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High dynamic range (HDR) images and video contain pixels, which can represent much greater range of colors and brightness levels than that offered by existing, standard dynamic range images. Such “better pixels” greatly improve the overall quality of visual content, making it appear much more realistic and appealing to the audience. HDR is one of the key technologies of the future imaging pipeline, which will change the way the digital visual content is represented and manipulated. This article offers a broad review of the HDR methods and technologies with an introduction to fundamental concepts behind the perception of HDR imagery. It serves as both an introduction to the subject and a review of the current state of the art in HDR imaging. It covers the topics related to capture of HDR content with cameras and its generation with computer graphics methods; encoding and compression of HDR images and video; tone mapping for displaying HDR content on standard dynamic range displays; inverse tone mapping for upscaling legacy content for presentation on HDR displays; the display technologies offering HDR range; and finally image and video quality metrics suitable for HDR content.

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Subband encoding of high dynamic range imagery

Cited by 62 publications

References 15 publications

Objective and subjective evaluation of High Dynamic Range video compression

Objective and subjective evaluation of High Dynamic Range video compression

On performance of lossless compression for HDR image quantized in color space

High Dynamic Range Imaging

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