Image display algorithms for high- and low-dynamic-range display devices

2007 ◽  
Vol 15 (12) ◽  
pp. 997 ◽  
Author(s):  
Erik Reinhard ◽  
Timo Kunkel ◽  
Yoann Marion ◽  
Jonathan Brouillat ◽  
Rémi Cozot ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Image Display ◽  
Display Devices ◽  
Display Algorithms ◽  
Low Dynamic Range

scholarly journals Temporal adaptation control for local tone mapping operator

2018 ◽  
Vol 69 (4) ◽  
pp. 261-269
Author(s):  
Dragomir El Mezeni ◽  
Lazar Saranovac
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Temporal Control ◽  
Display Devices ◽  
Flexible Control ◽  
Temporal Adaptation ◽  
Single Operator ◽  
Low Dynamic Range ◽  
Local Tone Mapping

Abstract High dynamic range (HDR) imaging has gained great popularity over the past twenty years. Tone mapping operator (TMO) is the key component that enables reproduction of HDR images on the standard low dynamic range (LDR) display devices. When it comes to the HDR video, design of the TMO becomes especially challenging since temporal control of TMO parameters is needed in order to avoid possible artifacts. Since temporal and spatial contrast cannot be met simultaneously, existing solutions are usually designed to optimize one of these two requirements. We present novel local tone mapping operator that preserves details and simultaneously provides good local and global contrast of processed images. Tunable temporal control enables trade-off between spatial and temporal contrast of a tone mapped video. Flexible control presented in this paper ensures that both requirements can be met with a single operator just by using different tuning of the control block.When compared to the state-of-the-art TMOs, proposed solution exhibits better results regarding overall image quality.

Creation Method of High Dynamic Range Image Based on Three-Color Camera

2015 ◽  
Vol 731 ◽  
pp. 193-196
Author(s):  
Jie Li ◽  
Hai Wen Wang ◽  
Xi Xi He
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Range Image ◽  
Range Images ◽  
Visual Evaluation ◽  
Display Devices ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
Detail Enhancement ◽  
Fine Tune

The current HDR (High-Dynamic Range) images gets expensive display devices with low dynamic range of equipment problems, research objectives are presented methods for using ordinary camera fetching and displaying high dynamic range images. General three-color camera’s use is to obtain 3 different exposures of the same scene images, and binary image pyramid, followed by low-level image panning and rotation registration step by step, using HDR Darkroom Photomatix software obtains high dynamic range images ,tone mapping and detail enhancement, using Photoshop software to fine-tune to get the final high-dynamic range images. Visual evaluation and instrumental measurements shows the synthesis of high dynamic range images can increase reflects the brightness of the scene, details and colour information, application and promotion of the value of the method.

Preliminary validation of a new variable pattern for daily quality assurance of medical image display devices

2007 ◽  
Vol 34 (7) ◽  
pp. 2744-2758 ◽  
Author(s):  
Jurgen Jacobs ◽  
Frank Rogge ◽  
John Kotre ◽  
Guy Marchal ◽  
Hilde Bosmans
Keyword(s):  
Quality Assurance ◽  
Medical Image ◽  
Image Display ◽  
Display Devices ◽  
Variable Pattern ◽  
Preliminary Validation

Depth Estimation for HDR Images

2012 ◽  
pp. 165-180
Author(s):  
S. Manikandan
Keyword(s):  
Dynamic Range ◽  
Depth Estimation ◽  
High Dynamic Range ◽  
Block Matching ◽  
Absolute Difference ◽  
Mapping Technique ◽  
Stereo Pair ◽  
Block Matching Algorithm ◽  
High Dynamic ◽  
Low Dynamic Range

In this chapter, depth estimation for stereo pair of High Dynamic Range (HDR) images is proposed. The proposed algorithm consists of two major techniques namely conversion of HDR images to Low Dynamic Range (LDR) images or Standard Dynamic Range (SDR) images and estimating the depth from the converted LDR / SDR stereo images. Local based tone mapping technique is used for the conversion of the HDR images to SDR images. And the depth estimation is done based on the corner features of the stereo pair images and block matching algorithm. Computationally much less expensive cost functions Mean Square Error (MSE) or Mean Absolute Difference (MAD) can be used for block matching algorithms. The proposed algorithm is explained with illustrations and results.

A Contribution Algorithm from LDRI to HDRI

2019 ◽  
Vol 34 (07) ◽  
pp. 2059025
Author(s):  
Junsong Luo ◽  
Shi Qiu ◽  
Yizhang Jiang ◽  
Keyang Cheng ◽  
Huping Ye ◽  
...  
Keyword(s):  
Response Curve ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Image Sequences ◽  
Range Image ◽  
High Dynamic Range Image ◽  
Dynamic Image ◽  
High Dynamic ◽  
Low Dynamic Range ◽  
First Time

High dynamic range image (HDRI) which is combined with low dynamic range image (LDRI) needs to be mapped to a low dynamic area to display. In the process of mapping, it is impossible to determine the contribution of low dynamic image sequences in the display images, so that it results in a problem that the low dynamic images cannot be accurately selected. In this paper, for the first time, a contribution algorithm from LDRI to HDRI according to the corresponding response curve of the camera is proposed.

scholarly journals Extending and Matching a High Dynamic Range Image from a Single Image

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3950
Author(s):  
Van Luan Tran ◽  
Huei-Yung Lin
Keyword(s):  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Performance Comparison ◽  
Range Image ◽  
High Dynamic Range Image ◽  
High Dynamic ◽  
The Difference ◽  
Imaging Algorithms ◽  
Low Dynamic Range

Extending the dynamic range can present much richer contrasts and physical information from the traditional low dynamic range (LDR) images. To tackle this, we propose a method to generate a high dynamic range image from a single LDR image. In addition, a technique for the matching between the histogram of a high dynamic range (HDR) image and the original image is introduced. To evaluate the results, we utilize the dynamic range for independent image quality assessment. It recognizes the difference in subtle brightness, which is a significant role in the assessment of novel lighting, rendering, and imaging algorithms. The results show that the picture quality is improved, and the contrast is adjusted. The performance comparison with other methods is carried out using the predicted visibility (HDR-VDP-2). Compared to the results obtained from other techniques, our extended HDR images can present a wider dynamic range with a large difference between light and dark areas.

Sign in / Sign up

Export Citation Format

Share Document