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

Methods for Improving the Tone Mapping for Backward Compatible High Dynamic Range Image and Video Coding

International audienceBackward compatibility for high dynamic range image and video compression forms one of the essential requirements in the transition phase from low dynamic range (LDR) displays to high dynamic range (HDR) displays. In a recent work [1], the problems of tone mapping and HDR video coding are originally fused together in the same mathematical framework, and an optimized solution for tone mapping is achieved in terms of the mean square error (MSE) of the logarithm of luminance values. In this paper, we improve this pioneer study in three aspects by considering its three shortcomings. First, the proposed method [1] works over the logarithms of luminance values which are not uniform with respect to Human Visual System (HVS) sensitivity. We propose to use the perceptually uniform luminance values as an alternative for the optimization of tone mapping curve. Second, the proposed method [1] does not take the quality of the resulting tone mapped images into account during the formulation in contrary to the main goal of tone mapping research. We include the LDR image quality as a constraint to the optimization problem and develop a generic methodology to compromise the trade-off between HDR and LDR image qualities for coding. Third, the proposed method [1] simply applies a low-pass filter to the generated tone curves for video frames to avoid flickering during the adaptation of the method to the video. We instead include an HVS based flickering constraint to the optimization and derive a methodology to compromise the trade-off between the rate-distortion performance and flickering distortion. The superiority of the proposed methodologies is verified with experiments on HDR images and video sequences

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

Objective and subjective evaluation of High Dynamic Range video compression

A 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

A JPEG backward-compatible HDR image compression

High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularity and full public adoption of HDR content is however hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of Low Dynamic Range (LDR) displays that are unable to render HDR. To facilitate wide spread of HDR usage, the backward compatibility of HDR technology with commonly used legacy image storage, rendering, and compression is necessary. Although many tone-mapping algorithms were developed for generating viewable LDR images from HDR content, there is no consensus on which algorithm to use and under which conditions. This paper, via a series of subjective evaluations, demonstrates the dependency of perceived quality of the tone-mapped LDR images on environmental parameters and image content. Based on the results of subjective tests, it proposes to extend JPEG file format, as the most popular image format, in a backward compatible manner to also deal with HDR pictures. To this end, the paper provides an architecture to achieve such backward compatibility with JPEG and demonstrates efficiency of a simple implementation of this framework when compared to the state of the art HDR image compression

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display

Head mounted displays are characterized by relatively low resolution and low dynamic range. These limitations significantly reduce the visual quality of photo-realistic captures on such displays. This thesis presents an interactive view optimized tone mapping technique for viewing large sized high dynamic range panoramas up to 16384 by 8192 on head mounted displays. This technique generates a separate file storing pre-computed view-adjusted mapping function parameters. We define this technique as ToneTexture. The use of a view adjusted tone mapping allows for expansion of the perceived color space available to the end user. This yields an improved visual appearance of both high dynamic range panoramas and low dynamic range panoramas on such displays. Moreover, by providing proper interface to manipulate on ToneTexture, users are allowed to adjust the mapping function as to changing color emphasis. The authors present comparisons of the results produced by ToneTexture technique against widely-used Reinhard tone mapping operator and Filmic tone mapping operator both objectively via a mathematical quality assessment metrics and subjectively through user study. Demonstration systems are available for desktop and head mounted displays such as Oculus Rift and GearVR

Inverse tone mapping

The introduction of High Dynamic Range Imaging in computer graphics has produced a novelty in Imaging that can be compared to the introduction of colour photography or even more. Light can now be captured, stored, processed, and finally visualised without losing information. Moreover, new applications that can exploit physical values of the light have been introduced such as re-lighting of synthetic/real objects, or enhanced visualisation of scenes. However, these new processing and visualisation techniques cannot be applied to movies and pictures that have been produced by photography and cinematography in more than one hundred years. This thesis introduces a general framework for expanding legacy content into High Dynamic Range content. The expansion is achieved avoiding artefacts, producing images suitable for visualisation and re-lighting of synthetic/real objects. Moreover, it is presented a methodology based on psychophysical experiments and computational metrics to measure performances of expansion algorithms. Finally, a compression scheme, inspired by the framework, for High Dynamic Range Textures, is proposed and evaluated