2,347 research outputs found
Digital Color Imaging
This paper surveys current technology and research in the area of digital
color imaging. In order to establish the background and lay down terminology,
fundamental concepts of color perception and measurement are first presented
us-ing vector-space notation and terminology. Present-day color recording and
reproduction systems are reviewed along with the common mathematical models
used for representing these devices. Algorithms for processing color images for
display and communication are surveyed, and a forecast of research trends is
attempted. An extensive bibliography is provided
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All-Inorganic Metal Halide Perovskite Nanocrystals: Opportunities and Challenges.
The past decade has witnessed the growing interest in metal halide perovskites as driven by their promising applications in diverse fields. The low intrinsic stability of the early developed organic versions has however hampered their widespread applications. Very recently, all-inorganic perovskite nanocrystals have emerged as a new class of materials that hold great promise for the practical applications in solar cells, photodetectors, light-emitting diodes, and lasers, among others. In this Outlook, we first discuss the recent developments in the preparation, properties, and applications of all-inorganic metal halide perovskite nanocrystals, with a particular focus on CsPbX3, and then provide our view of current challenges and future directions in this emerging area. Our goal is to introduce the current status of this type of new materials to researchers from different areas and motivate them to explore all the potentials
The development of local solar irradiance for outdoor computer graphics rendering
Atmospheric effects are approximated by solving the light transfer equation, LTE, of a given viewing path. The resulting accumulated spectral energy (its visible band) arriving at the observer’s eyes, defines the colour of the object currently on the line of sight. Due to the convenience of using a single rendering equation to solve the LTE for daylight sky and distant objects (aerial perspective), recent methods had opt for a similar kind of approach. Alas, the burden that the real-time calculation brings to the foil had forced these methods to make simplifications that were not in line with the actual world observation. Consequently, the results of these methods are laden with visual-errors. The two most common simplifications made were: i) assuming the atmosphere as a full-scattering medium only and ii) assuming a single density atmosphere profile. This research explored the possibility of replacing the real-time calculation involved in solving the LTE with an analytical-based approach. Hence, the two simplifications made by the previous real-time methods can be avoided. The model was implemented on top of a flight simulator prototype system since the requirements of such system match the objectives of this study. Results were verified against the actual images of the daylight skies. Comparison was also made with the previous methods’ results to showcase the proposed model strengths and advantages over its peers
Towards Efficient SDRTV-to-HDRTV by Learning from Image Formation
Modern displays are capable of rendering video content with high dynamic
range (HDR) and wide color gamut (WCG). However, the majority of available
resources are still in standard dynamic range (SDR). As a result, there is
significant value in transforming existing SDR content into the HDRTV standard.
In this paper, we define and analyze the SDRTV-to-HDRTV task by modeling the
formation of SDRTV/HDRTV content. Our analysis and observations indicate that a
naive end-to-end supervised training pipeline suffers from severe gamut
transition errors. To address this issue, we propose a novel three-step
solution pipeline called HDRTVNet++, which includes adaptive global color
mapping, local enhancement, and highlight refinement. The adaptive global color
mapping step uses global statistics as guidance to perform image-adaptive color
mapping. A local enhancement network is then deployed to enhance local details.
Finally, we combine the two sub-networks above as a generator and achieve
highlight consistency through GAN-based joint training. Our method is primarily
designed for ultra-high-definition TV content and is therefore effective and
lightweight for processing 4K resolution images. We also construct a dataset
using HDR videos in the HDR10 standard, named HDRTV1K that contains 1235 and
117 training images and 117 testing images, all in 4K resolution. Besides, we
select five metrics to evaluate the results of SDRTV-to-HDRTV algorithms. Our
final results demonstrate state-of-the-art performance both quantitatively and
visually. The code, model and dataset are available at
https://github.com/xiaom233/HDRTVNet-plus.Comment: Extended version of HDRTVNe
Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display
ITM(inverse tone-mapping) converts SDR (standard dynamic range) footage to
HDR/WCG (high dynamic range /wide color gamut) for media production. It happens
not only when remastering legacy SDR footage in front-end content provider, but
also adapting on-theair SDR service on user-end HDR display. The latter
requires more efficiency, thus the pre-calculated LUT (look-up table) has
become a popular solution. Yet, conventional fixed LUT lacks adaptability, so
we learn from research community and combine it with AI. Meanwhile,
higher-bit-depth HDR/WCG requires larger LUT than SDR, so we consult
traditional ITM for an efficiency-performance trade-off: We use 3 smaller LUTs,
each has a non-uniform packing (precision) respectively denser in dark, middle
and bright luma range. In this case, their results will have less error only in
their own range, so we use a contribution map to combine their best parts to
final result. With the guidance of this map, the elements (content) of 3 LUTs
will also be redistributed during training. We conduct ablation studies to
verify method's effectiveness, and subjective and objective experiments to show
its practicability. Code is available at: https://github.com/AndreGuo/ITMLUT.Comment: Accepted in CVMP2023 (the 20th ACM SIGGRAPH European Conference on
Visual Media Production
High Dynamic Range Imaging Technology.
Abstract:
In this lecture note, we describe high dynamic range (HDR) imaging systems. Such systems are able to represent luminances of much larger brightness and, typically, a larger range of colors than conventional standard dynamic range (SDR) imaging systems. The larger luminance range greatly improves the overall quality of visual content, making it appear much more realistic and appealing to observers. HDR is one of the key technologies in the future imaging pipeline, which will change the way the digital visual content is represented and manipulated today
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