Luminance adaptation transform based on brightness functions for LDR image reproduction

Kwon, Hyunwook; Lee, Sung Hak; Lee, Geun-Young; Sohng, Kyu‐Ik

doi:10.1016/j.dsp.2014.03.008

Cited by 27 publications

(21 citation statements)

References 13 publications

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“…The iCAM06 applies the Stevens effect to enhance the detail layer, but the Stevens effect is not suitable for complex scenes such as images because it explains the relationship between brightness and luminance for a simple target [13]. Bartleson and Breneman examined the brightness perception in a complex field.…”

Section: Appl Sci 2020 10 X For Peer Review 3 Of 13mentioning

confidence: 99%

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Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging

Kwon

Lee

2020

Applied Sciences

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High dynamic range (HDR) imaging is used to represent scenes with a greater dynamic range of luminance on a standard dynamic range display. Usually, HDR images are synthesized through base–detail separations. The base layer is used for tone compression and the detail layer is used for detail preservation. The representative detail-preserved algorithm iCAM06 has a tendency to reduce the sharpness of dim surround images, because of the fixed edge-stopping function of the fast-bilateral filter (FBF). This paper proposes a novel base–detail separation and detail compensation technique using the contrast sensitivity function (CSF) in the segmented frequency domain. Experimental results show that the proposed rendering method has better sharpness features and image quality than previous methods correlated by the human visual system.

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Section: Appl Sci 2020 10 X For Peer Review 3 Of 13mentioning

confidence: 99%

“…Proposed CSF and CSF sensitivity gain graphs. (a) Relative CSF graphs in Equation(4)and (b) CSF sensitivity gain graphs in Equation(13).…”

mentioning

confidence: 99%

Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging

Kwon

Lee

2020

Applied Sciences

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“…For instance, there are recent studies on color calibration [6], and on the appearance of colors on electronic devices when used under high ambient lighting conditions [7]. Other approaches investigate the effect of the paper properties on the color reproduction in digital printing [8], or propose visual brightness functions to enhance the contrast and saturation of rendered images [9]. From the industry perspective, there are several applications to control and guarantee that colors are reproduced accurately.…”

Section: Introductionmentioning

confidence: 99%

A Neural System for Faithful Color Reproduction in Industrial Printing Processes

Lazzerini

Pistolesi

2018

2018 International Joint Conference on Neural Networks (IJCNN)

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Printing is a widespread industrial process. Manufacturers of colored products are expected to maintain high levels of color quality to perfectly satisfy the customers' requirements. The rendering of colors is visually checked by experienced workers, who may though show different color sensitiveness, depending, e.g., on perceptual, cognitive and cultural aspects. This often results in products that fail to faithfully reproduce what the customer asked for, with negative consequences for companies, as well as huge financial losses. This paper describes a neural network-based system to objectively check how faithfully colors are reproduced by an industrial printing process. The system considers a master color, then compares it to a copy, and returns an objective degree of color fidelity of the copy to the master. The neural system was trained and tested in a real-world case study by using a huge quantity of color pairs taken from the L*a*b* color space. Highly accurate results were achieved. The strengths of the system are that it can measure the difference of colors in a way that is incredibly close to that perceived by the human eye, and the fact that it can do that canceling the color distortion phenomena that may occur in the human vision.

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“…The single‐scale method depends on a surround map with Gaussian blurring. A narrow Gaussian filter enhances the local details; however, it reduces the global rendition and increases the halo artefacts, whereas a wide Gaussian filter has the opposite tendency [15]. The multi‐scale method properly combines the detail rendition with the narrow blur filter and the global rendition with the wide blur filter.…”

Section: Introductionmentioning

confidence: 99%

Enhanced high dynamic‐range image rendering using a surround map based on edge‐adaptive layer blurring

Kwon

Lee

et al. 2016

IET Computer Vision

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Many tone‐mapping methods have developed efficient tone compression and local contrast enhancement techniques for high dynamic‐range imaging. Local tone mapping enhances the image quality to reveal the details; however, it causes artefacts such as halos. Halo artefacts appear around the edges of an image and lead to deterioration in the overall image quality. Detail‐base separation and multi‐scale methods have been developed to reduce halo artefacts. Detail‐base separation methods divide the image into a detail layer and base layer using an edge‐preserving filter and process each layer independently. Multi‐scale methods alleviate artefacts such as halos, noise, and awkward global toning using a weighted sum of single‐scale images. These methods have several inherent problems including the complexity of the edge‐preserving filter and multi‐processing redundancy. Therefore, in this study, a novel surround map is presented to resolve halo artefacts and enhance local details in single‐scale processing.

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Luminance adaptation transform based on brightness functions for LDR image reproduction

Cited by 27 publications

References 13 publications

Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging

Contrast Sensitivity Based Multiscale Base–Detail Separation for Enhanced HDR Imaging

A Neural System for Faithful Color Reproduction in Industrial Printing Processes

Enhanced high dynamic‐range image rendering using a surround map based on edge‐adaptive layer blurring

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