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.

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 No-reference Automatic Quality Assessment for Colorfulness-Adjusted, Contrast-Adjusted, and Sharpness-Adjusted Images Using High-Dynamic-Range-Derived Features

2018 ◽  
Vol 8 (9) ◽  
pp. 1688 ◽  
Author(s):  
Jinseong Jang ◽  
Hanbyol Jang ◽  
Taejoon Eo ◽  
Kihun Bang ◽  
Dosik Hwang
Keyword(s):  
Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Assessment Methods ◽  
Reference Image ◽  
Range Images ◽  
Automatic Assessment ◽  
Visual Preference ◽  
Subjective Evaluations ◽  
High Dynamic

Image adjustment methods are one of the most widely used post-processing techniques for enhancing image quality and improving the visual preference of the human visual system (HVS). However, the assessment of the adjusted images has been mainly dependent on subjective evaluations. Also, most recently developed automatic assessment methods have mainly focused on evaluating distorted images degraded by compression or noise. The effects of the colorfulness, contrast, and sharpness adjustments on images have been overlooked. In this study, we propose a fully automatic assessment method that evaluates colorfulness-adjusted, contrast-adjusted, and sharpness-adjusted images while considering HVS preferences. The proposed method does not require a reference image and automatically calculates quantitative scores, visual preference, and quality assessment with respect to the level of colorfulness, contrast, and sharpness adjustment. The proposed method evaluates adjusted images based on the features extracted from high dynamic range images, which have higher colorfulness, contrast, and sharpness than that of low dynamic range images. Through experimentation, we demonstrate that our proposed method achieves a higher correlation with subjective evaluations than that of conventional assessment methods.

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