HIGH DYNAMIC RANGE IMAGE AND VIDEO COMPRESSION- FIDELITY MATCHING HUMAN VISUAL PERFORMANCE

Vast majority of digital images and video material stored today can capture only a fraction of visual information visible to the human eye and does not offer sufficient quality to fully exploit capabilities of new display devices. High dynamic range (HDR) image and video formats encode the full visible range of luminance and color gamut, thus offering ultimate fidelity, limited only by the capabilities of the human eye and not by any existing technology. In this paper we demonstrate how existing image and video compression standards can be extended to encode HDR content efficiently. This is achieved by a custom color space for encoding HDR pixel values that is derived from the visual performance data. We also demonstrate how HDR image and video compression can be designed so that it is backward compatible with existing formats. Index Terms — HDR, high dynamic range, video coding, MPEG, color space, backward-compatible coding, scenereferred, output-referred 1

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

High dynamic range imaging implementation in scene monitoring under bad illumination

Unapređenje kvaliteta slike širenjem dinamičkog opsega u poslednje vreme se intenzivno koristi. Ovo za posledicu ima prisustvo znatno više detalja na slici, što je jako bitno u većini primena. Širenje dinamičkog opsega ima svoje granice i one su definisane fizičkim limitima senzora koji se koristi, tj. ograničenjima njegovog A/D konvertora. Kada je dinamički opseg scene značajno širi od dinamičkog opsega senzora, mnogi detalji neće biti adekvatno prikazani na slici. Međutim, ukoliko senzor inherentno podržava široki dinamički opseg, jasno se može uočiti da je snimljena slika kvalitetnija od one koja se dobija sa standardnog senzora...Improving image quality by expanding the dynamic range is extensively used recently. This results in the presence of significantly more details in the picture, which is very important for most applications. Expanding the dynamic range has its limits, and they are defined by the physical limits of sensor used, i.e. the limits of its A / D converter. When the dynamic range of the scene is significantly wider than the dynamic range of the sensor, many details will not be shown properly in the picture. However, if the sensor inherently supports wide dynamic range, it can be clearly noticed that the recorded image quality is higher than the one obtained with the standard sensors..