388 research outputs found
Scene-based imperceptible-visible watermarking for HDR video content
This paper presents the High Dynamic Range - Imperceptible Visible Watermarking for HDR video content (HDR-IVW-V) based on scene detection for robust copyright protection of HDR videos using a visually imperceptible watermarking methodology. HDR-IVW-V employs scene detection to reduce both computational complexity and undesired visual attention to watermarked regions. Visual imperceptibility is achieved by finding the region of a frame with the highest hiding capacities on which the Human Visual System (HVS) cannot recognize the embedded watermark. The embedded watermark remains visually imperceptible as long as the normal color calibration parameters are held. HDR-IVW-V is evaluated on PQ-encoded HDR video content successfully attaining visual imperceptibility, robustness to tone mapping operations and image quality preservation
Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments
© 2016 In this paper, we present a new technique for displaying High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays in an efficient way on the GPU. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as the reference that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO. Finally, we present a GPU version, which is perceptually equal to the standard version but with much improved computational performance
Optimal exposure compression for high dynamic range content
High dynamic range (HDR) imaging has become one of the foremost imaging methods capable of capturing and displaying the full range of lighting perceived by the human visual system in the real world. A number of HDR compression methods for both images and video have been developed to handle HDR data, but none of them has yet been adopted as the method of choice. In particular, the backwards-compatible methods that always maintain a stream/image that allow part of the content to be viewed on conventional displays make use of tone mapping operators which were developed to view HDR images on traditional displays. There are a large number of tone mappers, none of which is considered the best as the images produced could be deemed subjective. This work presents an alternative to tone mapping-based HDR content compression by identifying a single exposure that can reproduce the most information from the original HDR image. This single exposure can be adapted to fit within the bit depth of any traditional encoder. Any additional information that may be lost is stored as a residual. Results demonstrate quality is maintained as well, and better, than other traditional methods. Furthermore, the presented method is backwards-compatible, straightforward to implement, fast and does not require choosing tone mappers or settings
Stereoscopic high dynamic range imaging
Two modern technologies show promise to dramatically increase immersion in
virtual environments. Stereoscopic imaging captures two images representing
the views of both eyes and allows for better depth perception. High dynamic
range (HDR) imaging accurately represents real world lighting as opposed to
traditional low dynamic range (LDR) imaging. HDR provides a better contrast
and more natural looking scenes. The combination of the two technologies in
order to gain advantages of both has been, until now, mostly unexplored due to
the current limitations in the imaging pipeline. This thesis reviews both fields,
proposes stereoscopic high dynamic range (SHDR) imaging pipeline outlining the
challenges that need to be resolved to enable SHDR and focuses on capture and
compression aspects of that pipeline.
The problems of capturing SHDR images that would potentially require two
HDR cameras and introduce ghosting, are mitigated by capturing an HDR and
LDR pair and using it to generate SHDR images. A detailed user study compared
four different methods of generating SHDR images. Results demonstrated that
one of the methods may produce images perceptually indistinguishable from the
ground truth.
Insights obtained while developing static image operators guided the design
of SHDR video techniques. Three methods for generating SHDR video from an
HDR-LDR video pair are proposed and compared to the ground truth SHDR
videos. Results showed little overall error and identified a method with the least
error.
Once captured, SHDR content needs to be efficiently compressed. Five SHDR
compression methods that are backward compatible are presented. The proposed
methods can encode SHDR content to little more than that of a traditional single
LDR image (18% larger for one method) and the backward compatibility property
encourages early adoption of the format.
The work presented in this thesis has introduced and advanced capture and
compression methods for the adoption of SHDR imaging. In general, this research
paves the way for a novel field of SHDR imaging which should lead to improved
and more realistic representation of captured scenes
Towards Robust SDRTV-to-HDRTV via Dual Inverse Degradation Network
Recently, the transformation of standard dynamic range TV (SDRTV) to high
dynamic range TV (HDRTV) is in high demand due to the scarcity of HDRTV
content. However, the conversion of SDRTV to HDRTV often amplifies the existing
coding artifacts in SDRTV which deteriorate the visual quality of the output.
In this study, we propose a dual inverse degradation SDRTV-to-HDRTV network
DIDNet to address the issue of coding artifact restoration in converted HDRTV,
which has not been previously studied. Specifically, we propose a
temporal-spatial feature alignment module and dual modulation convolution to
remove coding artifacts and enhance color restoration ability. Furthermore, a
wavelet attention module is proposed to improve SDRTV features in the frequency
domain. An auxiliary loss is introduced to decouple the learning process for
effectively restoring from dual degradation. The proposed method outperforms
the current state-of-the-art method in terms of quantitative results, visual
quality, and inference times, thus enhancing the performance of the
SDRTV-to-HDRTV method in real-world scenarios.Comment: 10 page
Algorithms for compression of high dynamic range images and video
The recent advances in sensor and display technologies have brought upon the High Dynamic Range (HDR) imaging capability. The modern multiple exposure HDR sensors can achieve the dynamic range of 100-120 dB and LED and OLED display devices have contrast ratios of 10^5:1 to 10^6:1.
Despite the above advances in technology the image/video compression algorithms and associated hardware are yet based on Standard Dynamic Range (SDR) technology, i.e. they operate within an effective dynamic range of up to 70 dB for 8 bit gamma corrected images. Further the existing infrastructure for content distribution is also designed for SDR, which creates interoperability problems with true HDR capture and display equipment.
The current solutions for the above problem include tone mapping the HDR content to fit SDR. However this approach leads to image quality associated problems, when strong dynamic range compression is applied. Even though some HDR-only solutions have been proposed in literature, they are not interoperable with current SDR infrastructure and are thus typically used in closed systems.
Given the above observations a research gap was identified in the need for efficient algorithms for the compression of still images and video, which are capable of storing full dynamic range and colour gamut of HDR images and at the same time backward compatible with existing SDR infrastructure. To improve the usability of SDR content it is vital that any such algorithms should accommodate different tone mapping operators, including those that are spatially non-uniform.
In the course of the research presented in this thesis a novel two layer CODEC architecture is introduced for both HDR image and video coding. Further a universal and computationally efficient approximation of the tone mapping operator is developed and presented. It is shown that the use of perceptually uniform colourspaces for internal representation of pixel data enables improved compression efficiency of the algorithms. Further proposed novel approaches to the compression of metadata for the tone mapping operator is shown to improve compression performance for low bitrate video content. Multiple compression algorithms are designed, implemented and compared and quality-complexity trade-offs are identified. Finally practical aspects of implementing the developed algorithms are explored by automating the design space exploration flow and integrating the high level systems design framework with domain specific tools for synthesis and simulation of multiprocessor systems. The directions for further work are also presented
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