The Quantitative Model for Optimal Threshold and Gamma of Display Using Brightness Function

Lee, Sung Hak; Jang, Soo-Wook; Kim, Eun-Su; Sohng, Kyu‐Ik

doi:10.1093/ietfec/e89-a.6.1720

Cited by 14 publications

(10 citation statements)

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“…(a) is a collection of several original HDRIs. (b) is a collection of the resulting images by Equation (17). The attentional gaze is efficiently extracted as shown in the resulting images.…”

Section: Estimation Of Detail Layermentioning

confidence: 99%

“…The base layer is used to acquire global tone mapping, which contributes to compressing the dynamic range, as well as preserving sharp edges in the given HDRIs. The proposed TMO is a combination of two parameters [16,17]: key value of scene and visual gamma. Key value of scene is intended to scale the contrast (or brightness) of the given HDRI whereas visual gamma is designed to compress the dynamic range based on the contrast sensitivity function (CSF) [18].…”

Section: Introductionmentioning

confidence: 99%

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Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection

2019

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One of the significant qualities of the human vision, which differentiates it from computer vision, is so called attentional control, which is the innate ability of our human eyes to select what visual stimuli to pay attention to at any moment in time. In this sense, the visual salience detection model, which is designed to simulate how the human visual system (HVS) perceives objects and scenes, is widely used for performing multiple vision tasks. This model is also in high demand in the tone mapping technology of high dynamic range images (HDRIs). Another distinct quality of the HVS is that our eyes blink and adjust brightness when objects are in their sight. Likewise, HDR imaging is a technology applied to a camera that takes pictures of an object several times by repeatedly opening and closing a camera iris, which is referred to as multiple exposures. In this way, the computer vision is able to control brightness and depict a range of light intensities. HDRIs are the product of HDR imaging. This article proposes a novel tone mapping method using CCH-based saliency-aware weighting and edge-aware weighting methods to efficiently detect image salience information in the given HDRIs. The two weighting methods combine with a guided filter to generate a modified guided image filter (MGIF). The function of the MGIF is to split an image into the base layer and the detail layer which are the two elements of an image: illumination and reflection, respectively. The base layer is used to obtain global tone mapping and compress the dynamic range of HDRI while preserving the sharp edges of an object in the HDRI. This has a remarkable effect of reducing halos in the resulting HDRIs. The proposed approach in this article also has several distinct advantages of discriminative operation, tolerance to image size variation, and minimized parameter tuning. According to the experimental results, the proposed method has made progress compared to its existing counterparts when it comes to subjective and quantitative qualities, and color reproduction.

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Section: Estimation Of Detail Layermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection

2019

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“…To address this problem, Lee et al obtained a curve representing the relation between threshold luminance and adapting luminance for constant brightness perception using the Stevens' results and Bartlenson-Breneman's functions. 19 As shown in Fig. 3, the curve represents the highest and lowest luminance perceived by human vision at each adapting luminance.…”

Section: Luminance-adaptive Human Vision Factorsmentioning

confidence: 99%

“…1,19 In the experimental results of Bartleson and Breneman for complex stimuli, the exponent of the lightness function increases with increasing adapting luminance, so photographic images require gamma correction based on the estimated visual gamma. Photographic images typically viewed in dim surroundings are reproduced using a power function with a lower exponent value.…”

Section: Visual Gamma Correctionmentioning

confidence: 99%

Visual sensitivity correlated tone reproduction for low dynamic range images in the compression field

Lee

Kwon

et al. 2014

Opt. Eng

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Abstract. An image toning method for low dynamic range image compression is presented. The proposed method inserts tone mapping into JPEG baseline instead of postprocessing. First, an image is decomposed into detail, base, and surrounding components in terms of the discrete cosine transform coefficients. Subsequently, a luminance-adaptive tone mapping based on the human visual sensitivity properties is applied. In addition, compensation modules are added to enhance the visually sensitive factors, such as saturation, sharpness, and gamma. A comparative study confirms that the transmitted compression images have good image quality. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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“…Since image sticking is perceived by different luminance, the contrast sensitivity of human vision plays a critical role in evaluating how serious the image sticking is. Physiologically, the contrast sensitivity is defined as the least luminance difference that can be distinguished by human [3,4]. The smaller the least perceivable luminance difference is, the higher the contrast sensitivity is.…”

Section: Evaluation Of Image Stickingmentioning

confidence: 99%

P‐159: Releasing Behavior of Image Sticking

Chen

Liu

Liao

et al. 2008

Symp Digest of Tech Papers

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The Quantitative Model for Optimal Threshold and Gamma of Display Using Brightness Function

Cited by 14 publications

References 0 publications

Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection

Tone Mapping of High Dynamic Range Images Combining Co-Occurrence Histogram and Visual Salience Detection

Visual sensitivity correlated tone reproduction for low dynamic range images in the compression field

P‐159: Releasing Behavior of Image Sticking

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