scholarly journals Edge Detection technique based on HDR image quality assessment

2021 ◽  
Vol 2078 (1) ◽  
pp. 012029
Author(s):  
Dingxian Wang
Keyword(s):  
Image Quality ◽  
Edge Detection ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Edge Information ◽  
Image Edge Detection ◽  
Image Edge ◽  
Hdr Image

Abstract Image edge detection is one of the major study aspects in current computer image processing field. The quality of the input images is uneven, some have large fuzzy areas, some are underexposed, and the edges of objects in the images are difficult to detect, and the application scenarios of image edge detection are limited. In the view of the above problems, this paper has proposed that by applying High Dynamic Range (HDR) image quality assessment technology, combining multiple images with different exposures into one HDR image with detailed edge information, This technology effectively solved problem of low edge information richness, improved the effectiveness of edge detection algorithms, and contributed to the development of edge detection technology.

High Dynamic Range (HDR) Image Quality Assessment: A Survey

2019 ◽  
Author(s):  
Irwan Prasetya Gunawan ◽  
Ocarina Cloramidina ◽  
Salmaa Badriatu Syafa'ah ◽  
Guson Prasamuarso Kuntarto ◽  
Berkah I Santoso
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Hdr Image

scholarly journals A review on high dynamic range (HDR) image quality assessment

2021 ◽  
Vol 14 (1) ◽  
pp. 1-17
Author(s):  
Irwan Prasetya Gunawan ◽  
Ocarina Cloramidina ◽  
Salmaa Badriatu Syafa’ah ◽  
Rizcy Hafivah Febriani ◽  
Guson Prasamuarso Kuntarto ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Hdr Image

scholarly journals Blind Tone-Mapped Image Quality Assessment Based on Regional Sparse Response and Aesthetics

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 850
Author(s):  
Zhouyan He ◽  
Mei Yu ◽  
Fen Chen ◽  
Zongju Peng ◽  
Haiyong Xu ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Assessment Method ◽  
Quality Assessment Method ◽  
Scene Information ◽  
Detail Loss ◽  
Low Dynamic Range

High dynamic range (HDR) images give a strong disposition to capture all parts of natural scene information due to their wider brightness range than traditional low dynamic range (LDR) images. However, to visualize HDR images on common LDR displays, tone mapping operations (TMOs) are extra required, which inevitably lead to visual quality degradation, especially in the bright and dark regions. To evaluate the performance of different TMOs accurately, this paper proposes a blind tone-mapped image quality assessment method based on regional sparse response and aesthetics (RSRA-BTMI) by considering the influences of detail information and color on the human visual system. Specifically, for the detail loss in a tone-mapped image (TMI), multi-dictionaries are first designed for different brightness regions and whole TMI. Then regional sparse atoms aggregated by local entropy and global reconstruction residuals are presented to characterize the regional and global detail distortion in TMI, respectively. Besides, a few efficient aesthetic features are extracted to measure the color unnaturalness of TMI. Finally, all extracted features are linked with relevant subjective scores to conduct quality regression via random forest. Experimental results on the ESPL-LIVE HDR database demonstrate that the proposed RSRA-BTMI method is superior to the existing state-of-the-art blind TMI quality assessment methods.

Sign in / Sign up

Export Citation Format

Share Document