Refine Search

New Search

Results: 3

(searched for: doi:10.13176/11.511)
Save to Scifeed
Page of 1
Articles per Page
by
Show export options
  Select all
, Adam Krzyzak
International Journal of Wavelets, Multiresolution and Information Processing, Volume 19; https://doi.org/10.1142/s0219691321500247

The publisher has not yet granted permission to display this abstract.
, Anil Kumar Tiwari
IET Image Processing, Volume 13, pp 1170-1180; https://doi.org/10.1049/iet-ipr.2018.5496

Abstract:
In this study, a reduced-reference image-quality-assessment (IQA) method for screen content images, named as feature-quality-index (FQI) is proposed. The proposed method is based on the fact that the human visual system is more sensitive towards change in features than intensity or structure. Reduced features from the reference and distorted images are first extracted. In order to find the preserved features in the distorted image, a feature matching process with a reduced number of distance calculations is proposed, namely reduced-distance method. To reflect the importance of the matched features and their distance, the inner product between the normalised scale and distance vector is obtained. Extensive comparisons are performed on two available benchmark databases namely SIQAD and QACS, with eight reduced-reference, and nine full-reference state-of-the-art IQA techniques to demonstrate the consistency, accuracy, and robustness of the proposed FQI. The subjective evaluation of mean opinion score shows that FQI outperforms the current state-of-the-art IQA techniques.
Dogancan Temel, Ghassan AlRegib
2016 IEEE International Conference on Image Processing (ICIP) pp 2047-2051; https://doi.org/10.1109/icip.2016.7532718

Abstract:
This paper presents a full-reference image quality estimator based on SIFT descriptor matching over reliability-weighted feature maps. Reliability assignment includes a smoothing operation, a transformation to perceptual color domain, a local normalization stage, and a spectral residual computation with global normalization. The proposed method ReSIFT is tested on the LIVE and the LIVE Multiply Distorted databases and compared with 11 state-of-the-art full-reference quality estimators. In terms of the Pearson and the Spearman correlation, ReSIFT is the best performing quality estimator in the overall databases. Moreover, ReSIFT is the best performing quality estimator in at least one distortion group in compression, noise, and blur category.
Page of 1
Articles per Page
by
Show export options
  Select all
Back to Top Top