Automatic Exact Histogram Specification for Contrast Enhancement and Visual System Based Quantitative Evaluation

Dichoptic tone mapping methods aim to leverage stereoscopic displays to increase visual detail and contrast in images and videos. These methods, which have been called both binocular tone mapping and dichoptic contrast enhancement , selectively emphasize contrast differently in the two eyes’ views. The visual system integrates these contrast differences into a unified percept, which is theorized to contain more contrast overall than each eye’s view on its own. As stereoscopic displays become increasingly common for augmented and virtual reality (AR/VR), dichoptic tone mapping is an appealing technique for imaging pipelines. We sought to examine whether a standard photographic technique, exposure bracketing, could be modified to enhance contrast similarly to dichoptic tone mapping. While assessing the efficacy of this technique with user studies, we also re-evaluated existing dichoptic tone mapping methods. Across several user studies; however, we did not find evidence that either dichoptic tone mapping or dichoptic exposures consistently increased subjective image preferences. We also did not observe improvements in subjective or objective measures of detail visibility. We did find evidence that dichoptic methods enhanced subjective 3D impressions. Here, we present these results and evaluate the potential contributions and current limitations of dichoptic methods for applications in stereoscopic displays.

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Optimized Contrast Enhancement for Infrared Images Based on Global and Local Histogram Specification

Remote Sensing ◽

10.3390/rs11070849 ◽

2019 ◽

Vol 11 (7) ◽

pp. 849 ◽

Cited By ~ 3

Author(s):

Chengwei Liu ◽

Xiubao Sui ◽

Xiaodong Kuang ◽

Yuan Liu ◽

Guohua Gu ◽

...

Keyword(s):

Contrast Enhancement ◽

Visual Quality ◽

Local Contrast ◽

Original Image ◽

Infrared Images ◽

Histogram Specification ◽

Block Based ◽

Global And Local ◽

2D Histogram

In this paper, an optimized contrast enhancement method combining global and local enhancement results is proposed to improve the visual quality of infrared images. Global and local contrast enhancement methods have their merits and demerits, respectively. The proposed method utilizes the complementary characteristics of these two methods to achieve noticeable contrast enhancement without artifacts. In our proposed method, the 2D histogram, which contains both global and local gray level distribution characteristics of the original image, is computed first. Then, based on the 2D histogram, the global and local enhanced results are obtained by applying histogram specification globally and locally. Lastly, the enhanced result is computed by solving an optimization equation subjected to global and local constraints. The pixel-wise regularization parameters for the optimization equation are adaptively determined based on the edge information of the original image. Thus, the proposed method is able to enhance the local contrast while preserving the naturalness of the original image. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms the block-based methods for improving the visual quality of infrared images.

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Dynamic contrast enhancement based on histogram specification

IEEE Transactions on Consumer Electronics ◽

10.1109/tce.2005.1561859 ◽

2005 ◽

Vol 51 (4) ◽

pp. 1300-1305 ◽

Cited By ~ 110

Author(s):

Chi-Chia Sun ◽

Shanq-Jang Ruan ◽

Mon-Chau Shie ◽

Tun-Wen Pai

Keyword(s):

Contrast Enhancement ◽

Dynamic Contrast Enhancement ◽

Histogram Specification

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Image contrast enhancement method based on display and human visual system characteristics

Applied Optics ◽

10.1364/ao.58.001813 ◽

2019 ◽

Vol 58 (7) ◽

pp. 1813 ◽

Cited By ~ 2

Author(s):

Guo Chen ◽

Li Li ◽

Weiqi Jin ◽

Mingcong Liu ◽

Feng Shi

Keyword(s):

Visual System ◽

Contrast Enhancement ◽

Human Visual System ◽

Image Contrast ◽

Image Contrast Enhancement ◽

Enhancement Method ◽

System Characteristics

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Human Visual System-aware Dimming Method Combining Pixel Compensation and Histogram Specification

KSII Transactions on Internet and Information Systems ◽

10.3837/tiis.2017.12.017 ◽

2017 ◽

Vol 11 (12) ◽

Keyword(s):

Visual System ◽

Human Visual System ◽

Histogram Specification

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Optimal CT Contrast Enhancement Protocol for the Fontan Pathway: An Analysis Based on a 15-year Single-center Experience

10.21203/rs.3.rs-621039/v1 ◽

2021 ◽

Author(s):

Hyun Woo Goo

Keyword(s):

Standard Deviation ◽

Contrast Agent ◽

Contrast Enhancement ◽

Quantitative Evaluation ◽

Characteristic Curve ◽

Low Contrast ◽

Group 3 ◽

Heterogeneous Enhancement ◽

Standard Deviations ◽

Noise Ratio

Abstract This retrospective study was performed to systemically compare several candidates for optimal contrast enhancement protocols of cardiothoracic CT dedicated for evaluating the Fontan pathway. Of 115 CT examinations from 89 patients, simultaneous injection of contrast agent via the arm and leg veins with 50% diluted contrast agent (group 1, n = 38), 60-second scan delay after leg vein injection (group 2, n = 41) or 3-minute scan delay (group 3, n = 36) was used to obtain optimal contrast enhancement. The degree and heterogeneity of cardiovascular enhancement, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively evaluated. Histogram-assisted semi-quantitative evaluation was performed for heterogeneous enhancement, and a cut-off value indicating heterogeneous enhancement was determined by comparing the standard deviations between the cases showing homogeneous and heterogeneous enhancement. Contrast enhancement of the Fontan pathway, the standard deviation measured in the Fontan pathway, SNR, and CNR were more frequently lower in group 3 compared to groups 1 and 2 (p < 0.001). Homogeneous enhancement of the Fontan pathway based on the histogram-assisted semi-quantitative evaluation was more frequently seen in group 3 compared to groups 1 and 2 (p < 0.043‒0.001). Receiver operating characteristic curve analysis demonstrated that the standard deviation was an excellent diagnostic test in determining the homogeneity of contrast enhancement (area under the curve = 0.991; 95% confidence interval, 0.988‒0.994; p < 0.001). Standard deviations > 105.1 HU could be considered to indicate heterogeneous enhancement with 73.2% sensitivity and 100.0% specificity. The protocol using a 3-minute scan delay best achieved homogeneous contrast enhancement in the Fontan pathway on cardiothoracic CT among the tested protocols. However, low contrast enhancement, SNR, and, CNR need to be improved.

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