Towards an automated soft proofing system using high dynamic range imaging and artificial neural networks

10.32920/ryerson.14664726.v1 ◽

2021 ◽

Author(s):

Nawar Fdhal

Keyword(s):

Closed Loop ◽

Dynamic Range ◽

Liquid Crystal Display ◽

High Dynamic Range ◽

Black Box ◽

Box Model ◽

Measuring Device ◽

High Dynamic ◽

Artificial Neural ◽

Soft Proofing

In this thesis, an adaptive mechanism for controlling the illumination is combined with a closed loop technique and the use of High Dynamic range (HDR) to generate a black box model that can simulate the hard proof of a given digital image. An adaptive Artificial Neural Network (ANN) was used to create the black box model, using the camera as a measuring device. The non-uniformity of the illumination in the viewing booth is typically a barrier in creating such a black box model since color appearance varies with location in the viewing booth. This issue was addressed in this thesis by compensation for viewing booth illumination using an inexpensive camera and a Liquid Crystal Display (LCD) projector. HDR was found to give a favourable representation that is more indicative of the image perceived by the operator, and was used as the basis for mapping the original image to the soft proof. A proof of concept was also developed to highlight the utility of the LCD projector based approach in providing a more broad range of varying intensity color illuminants (thus environments) under which a proof may be not only viewed, but modeled through the closed loop process. In this sense, a system has been developed to generate and provide custom soft proofs that can extend the functionality of the standard viewing booth. The proposed technique will open the doors to new automated systems that can be very beneficial to the printing industry.

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Product Review: High Dynamic Range Displays

Presence Teleoperators & Virtual Environments ◽

10.1162/pres.16.1.119 ◽

2007 ◽

Vol 16 (1) ◽

pp. 119-122 ◽

Cited By ~ 1

Author(s):

Patrick Ledda

Keyword(s):

Dynamic Range ◽

Liquid Crystal Display ◽

Contrast Ratio ◽

Luminance Level ◽

High Dynamic Range ◽

Natural World ◽

Adaptation Level ◽

Wide Range ◽

High Dynamic ◽

3D Software

In the natural world, the human eye is confronted with a wide range of colors and luminances. A surface lit by moonlight might have a luminance level of around 10−3 cd/m2, while surfaces lit during a sunny day could reach values larger than 105 cd/m2. A good quality CRT (cathode ray tube) or LCD (liquid crystal display) monitor is only able to achieve a maximum luminance of around 200 to 300 cd/m2 and a contrast ratio of not more than two orders of magnitude. In this context the contrast ratio or dynamic range is defined as the ratio of the highest to the lowest luminance. We call high dynamic range (HDR) images, those images (or scenes) in which the contrast ratio is larger than what a display can reproduce. In practice, any scene that contains some sort of light source and shadows is HDR. The main problem with HDR images is that they cannot be displayed, therefore although methods to create them do exist (by taking multiple photographs at different exposure times or using computer graphics 3D software for example) it is not possible to see both bright and dark areas simultaneously. (See Figure 1.) There is data that suggests that our eyes can see detail at any given adaptation level within a contrast of 10,000:1 between the brightest and darkest regions of a scene. Therefore an ideal display should be able to reproduce this range. In this review, we present two high dynamic range displays developed by Brightside Technologies (formerly Sunnybrook Technologies) which are capable, for the first time, of linearly displaying high contrast images. These displays are of great use for both researchers in the vision/graphics/VR/medical fields as well as professionals in the VFX/gaming/architectural industry.

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