scholarly journals Method for reconstructing a high dynamic range image based on a single-shot filtered low dynamic range image

2020 ◽  
Vol 28 (21) ◽  
pp. 31057
Author(s):  
Bin Liang ◽  
Dongdong Weng ◽  
Yihua Bao ◽  
Ziqi Tu ◽  
Le Luo
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Single Shot ◽  
Range Image ◽  
High Dynamic Range Image ◽  
High Dynamic ◽  
Low Dynamic Range

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.

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