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 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.

No-reference high-dynamic-range image quality assessment based on tensor decomposition and manifold learning

2018 ◽  
Vol 57 (4) ◽  
pp. 839 ◽  
Author(s):  
Feifan Guan ◽  
Gangyi Jiang ◽  
Yang Song ◽  
Mei Yu ◽  
Zongju Peng ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Manifold Learning ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
Tensor Decomposition ◽  
High Dynamic Range ◽  
Range Image ◽  
High Dynamic Range Image ◽  
High Dynamic

scholarly journals COMPRESSION OF HIGH DYNAMIC RANGE OF SAR IMAGES

2018 ◽  
pp. 51-57
Author(s):  
Yu. I. Golub
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Reference Image ◽  
Sar Images ◽  
Assessment Measure ◽  
High Dynamic ◽  
Selection Of

The paper presents results of our experiments on compression of the high dynamic range SAR images. The range is equal to 16-bit. Objectives of study were comparison of known approaches to compression of the high dynamic range images; selection of optimal parameters for compression algorithms, and selection of a no-reference measure for image quality assessment after compression. Tone-mapping transformations like gamma correction, Ashikhmin-operator, mu-transformation, as well as no-reference image quality assessment measures were tested. The results of the experiments are presented in the article. It was concluded that further research and analysis of various functions and approaches to compression of dynamic range of SAR images is necessary, since including in the article approaches do not give stable and positive results on all SAR images. It was also concluded that after transformation 16-bit images, it is very difficult to estimate which image is better, and it is necessary to use no-reference image quality assessment measure.

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