scholarly journals Edge-texture 2D image quality metrics suitable for evaluation of image interpolation algorithms

2015 ◽  
Vol 12 (2) ◽  
pp. 405-425 ◽  
Author(s):  
Sanja Maksimovic-Moicevic ◽  
Zeljko Lukac ◽  
Miodrag Temerinac
Keyword(s):  
Image Quality ◽  
Image Quality Assessment ◽  
Signal To Noise Ratio ◽  
Quality Measures ◽  
Weighting Factor ◽  
Quality Indices ◽  
Compression Algorithms ◽  
Full Reference ◽  
Step Algorithm ◽  
Perceptual Assessment

A new objective, full-reference metrics of image quality is proposed in this paper. It should match perceptual (subjective) image quality assessment in a better way. The proposed method consists of two quality measures which separately indicate image quality on edges and in texture areas which are calculated in a three-step algorithm. The ?soft mask? is initially found for separation in edge and texture areas. Then, two MSEs (mean square error) with corresponding two PSNRs (peak signal-to-noise ratio) for edge and texture are calculated using soft mask as the weighting factor. Finally, the obtained two PSNRs are re-calculated into the two quality indices for edges and texture. Additionally, the separation factor, defined as percentage of edge areas in image, is considered, describing the influence of the image content on perceptual assessment. The proposed 2D metrics is especially suited for evaluations of different interpolation and compression algorithms.

scholarly journals Using the Natural Scenes’ Edges for Assessing Image Quality Blindly and Efficiently

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Saifeldeen Abdalmajeed ◽  
Jiao Shuhong
Keyword(s):  
Image Quality ◽  
Image Quality Assessment ◽  
Signal To Noise Ratio ◽  
Structural Similarity ◽  
Natural Image ◽  
Natural Scenes ◽  
Signal To Noise ◽  
Enhanced Sensitivity ◽  
Full Reference ◽  
Distortion Type

Two real blind/no-reference (NR) image quality assessment (IQA) algorithms in the spatial domain are developed. To measure image quality, the introduced approach uses an unprecedented concept for gathering a set of novel features based on edges of natural scenes. The enhanced sensitivity of the human eye to the information carried by edge and contour of an image supports this claim. The effectiveness of the proposed technique in quantifying image quality has been studied. The gathered features are formed using both Weibull distribution statistics and two sharpness functions to devise two separate NR IQA algorithms. The presented algorithms do not need training on databases of human judgments or even prior knowledge about expected distortions, so they are real NR IQA algorithms. In contrast to the most general no-reference IQA, the model used for this study is generic and has been created in such a way that it is not specified to any particular distortion type. When testing the proposed algorithms on LIVE database, experiments show that they correlate well with subjective opinion scores. They also show that the introduced methods significantly outperform the popular full-reference peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) methods. Besides they outperform the recently developed NR natural image quality evaluator (NIQE) model.

scholarly journals Quaternion wavelet transform based full reference image quality assessment for multiply distorted images

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199430 ◽  
Author(s):  
Chaofeng Li ◽  
Yifan Li ◽  
Yunhao Yuan ◽  
Xiaojun Wu ◽  
Qingbing Sang
Keyword(s):  
Wavelet Transform ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Full Reference ◽  
Quaternion Wavelet Transform

A weighted full-reference image quality assessment based on visual saliency

2017 ◽  
Vol 43 ◽  
pp. 119-126 ◽  
Author(s):  
Yang Wen ◽  
Ying Li ◽  
Xiaohua Zhang ◽  
Wuzhen Shi ◽  
Lin Wang ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Visual Saliency ◽  
Reference Image ◽  
Full Reference
Sign in / Sign up

Export Citation Format

Share Document