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Research >> High-Dynamic-Range Imaging
DescriptionThe power of the human visual system to process wide ranges of intensities far exceeds the abilities of current imaging systems. Both cameras and displays are currently limited to a dynamic range (contrast) of between 300:1 to 1,000:1, while the human visual system can process a simultaneous dynamic range of 50,000:1 or more, and can adapt to a much larger range. In recent years, there has been a strong push to alleviate this situation by developing high-dynamic-range (HDR) display and camera hardware, as well as the supporting processing algorithms. A new generation of high dynamic range (HDR) display devices promises to provide life-like picture quality, thanks to an improved luminance/color dynamic range over the existing conventional display technology.
Researchers
Current projects:
Tone Mapping of High Dynamic Range Videos ( Stelios Ploumis ): We develop a novel tone mapping operator that is designed based on perceptual characterestics of Human Visual System.
SDR images resulted from our method are noise-free and brighter than the one obtained with prior tone mapping operators. Since the proposed method is a Global TMO,
it is thereby of low complexity and suitable for real time applications.
Inverse Tone Mapping of High Dynamic Range Videos ( Pedram Mohammadi ): Conversion of existing image and video content to High Dynamic Range (HDR) using inverse Tone Mapping Operators (iTMOs)
is expected to enable the HDR market and open new market opportunities for studios and content owners. We developed a high contrast video iTMO that addresses shortcomings of existing approaches,
yielding HDR video quality worth the expectations of the emerging HDR technology. Our approach is content adaptive and is able to convert SDR videos to HDR videos of any target dynamic range.
Our approach follows the Human Visual System (HVS) characteristic of being more sensitive to luminance changes in dark areas than bright and normal ones, mapping each of these areas accordingly.
Our proposed method outperforms existing iTMOs in terms of overall HDR visual quality.
Perceptual Quality Improvement of High Dynamic Range Videos ( Maryam Azimi ): Extended range of color and brightness range of HDR videos have introduced new challenges in its compression and tranmission.
We have developed new techniques to pre-process the HDR video content such that its color information are maintained while a higher compression efficiency is achieved. The visual quality of our
processed videos are also improved.
Past projects:
Optimizing a Tone Curve for Backward-Compatible High Dynamic Range
Image and Video Compression: For backward compatible high dynamic range (HDR) video compression,
the HDR sequence is reconstructed by inverse tone-mapping a compressed
low dynamic range (LDR) version of the original HDR content. We show that the appropriate choice of a tone-mapping operator
(TMO) can significantly improve the reconstructed HDR quality. We
develop a statistical model that approximates the distortion resulting
from the combined processes of tone-mapping and compression. Using
this model, we formulate a numerical optimization problem to find the
tone-curve that minimizes the expected mean square error (MSE) in the
reconstructed HDR sequence. We also develop a simplified model that
reduces the computational complexity of the optimization problem to a
closed-form solution. Performance evaluations show that the proposed
methods provide superior performance in terms of HDR MSE and SSIM
compared to existing tone-mapping schemes. It is also shown that the
LDR image quality resulting from the proposed methods matches that
produced by perceptually-based TMOs.
Visually-Favourable Tone-Mapping with High Compression Performance: We develop a tone-mapping operator (TMO) that considers the perceptual
quality of the tone-mapped image together with the compression
efficiency. The proposed TMO is formulated
as an optimization problem that incorporates statistical models of i)
the quality of the tone-mapped image given a desired TMO, ii) the base
layer bit-rate and iii) the enhancement layer bit-rate. The results
show that our method achieves high coding gain while maintaining good
quality tone-mapped images.
Correction of Clipped Pixels in Color Images: Conventional images store a very limited dynamic range of brightness. The true luma in the bright area of such images is often lost due to clipping. When clipping changes the R, G, B color ratios of a pixel, color distortion also occurs. We propose an algorithm to enhance both the luma and chroma of the clipped pixels. Our method is based on the strong chroma spatial correlation between clipped pixels and their surrounding unclipped area. Both objective and subjective experimental results show that our algorithm is very effective in restoring the color of clipped pixels. Inverse tone mapped HDR images are more plausible and realistic when converted from the desaturated LDR images than when converted directly from the clipped images.
High-Dyanmic-Range Video Tone Mapping: Tone Mapping Operators (TMOs)
approximate the appearance of High-Dynamic-Range (HDR) content in
standard displays. The few available video TMOs are computationally
complex versions of existing schemes developed for still images. We
introduce a fast method for video tone mapping that takes advantage of
the strong temporal correlation that is usually found in video
sequences. Each frame is divided into several blocks and we employ a
motion estimation scheme that searches for similar blocks in a
previously tone-mapped reference frame. The bilateral filter TMO is
employed for the reference frames, but any other TMO can be used with
our scheme. Experiments show that high-detailed tone-mapped content
can be created without the need of employing a complex TMO on every
frame.
Selected Publications:
- P. Mohammadi, M. T. Pourazad and P. Nasiopoulos, "A High Contrast Video Inverse Tone Mapping Operator for High Dynamic Range Applications," 2019 IEEE International Symposium on Circuits and Systems (ISCAS), Sapporo, Japan, 2019, pp. 1-5.
- P. Mohammadi, M. Azimi and M. T. Pourazad, "An Entropy-Based Inverse Tone Mapping Operator with Improved Color Accuracy for High Dynamic Range Applications," 2019 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 2019, pp. 1-2.
- M. Azimi et al., "Compression efficiency of HDR/LDR content," 2015 Seventh International Workshop on Quality of Multimedia Experience (QoMEX), Pylos-Nestoras, 2015, pp. 1-6.
- M. Azimi, R. Boitard, M. T. Pourazad and P. Nasiopoulos, "Performance evaluation of single layer HDR video transmission pipelines," in IEEE Transactions on Consumer Electronics, vol. 63, no. 3, pp. 267-276, August 2017.
- M. Azimi, R. Boitard, P. Nasiopoulos and M. T. Pourazad, "Visual color difference evaluation of standard color pixel representations for high dynamic range video compression," 2017 25th European Signal Processing Conference (EUSIPCO), Kos, 2017, pp. 1480-1484.
- S. Ploumis, R. Boitard, M. T. Pourazad and P. Nasiopoulos, "Perception-based Histogram Equalization for tone mapping applications," 2016 Digital Media Industry & Academic Forum (DMIAF), Santorini, 2016, pp. 11-16.
- L. Coria, P. Nasiopoulos, "Using Temporal Correlation for Fast and High-detailed Video Tone Mapping," IEEE International Conference on Imaging Systems and Techniques IST 2010, Thessaloniki, Greece, July 1-2, 2010, pages 329-332.
- Z. Mai, H. Mansour, R. Mantiuk, P. Nasiopoulos, R. Ward, W. Heidrich, "Optimizing a Tone Curve for Backward-Compatible High Dynamic Range Image/Video Compression," accepted in the IEEE Transactions on Image Processing (TIP).
- Z. Mai, H. Mansour, P. Nasiopoulos and R. Ward, " Visually-Favorable Tone-Mapping with High Compression Performance ", IEEE International Conference on Image Processing 2010 (ICIP 2010), Hong Kong, September 2010.
- Z. Mai, H. Mansour, R. Mantiuk, P. Nasiopoulos, R. Ward and W. Heidrich, "On-the-Fly Tone-Mapping for Backward-Compatible High Dynamic Range Image/Video Compression," IEEE International Symposium on Circuits and Systems (ISCAS 2010), May 2010.
- D. Xu, C. Doutre, and P. Nasiopoulos, "Saturated-Pixel Enhancement for Color Images," IEEE International Symposium on Circuits and Systems (ISCAS 2010), May 2010.
- D. Xu, C. Doutre, and P. Nasiopoulos, “Correction of Clipped Pixels in Color Images,” IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 3, pp. 333-344, Mar. 2011, doi:10.1109/TVCG.2010.63.