Title :
An Edge Weighted RS image Quality Evaluation Method
Author :
Lu, Qin ; Du, Liebo ; Xiao, Xuemin
Author_Institution :
.Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
The approaches for remote sensing (RS) image quality evaluation can be categorized by two different criteria. One is the subjective image quality testing based on many observers. The other is the objective image quality testing based on mathematical calculation. Compared with the subjective method, objective image quality testing is easier for implementation. However, the traditional objective image quality evaluation models, such as MSE and PSNR, do not consider the human vision characteristics and hence sometimes have very low consistency with the subjective image quality testing results. To solve this problem, an objective evaluation model with a new evaluation index, named edge weighted peak signal noise ratio (EWPSNR), is proposed in this paper. Taking into account the human vision characteristics, the proposed objective evaluation model pays more attention to the edge distortion of the image. A weighting factor corresponding with the edge zone union of the original RS image and the reconstructed one is introduced into the model. Subjective method, PSNR based objective method and the proposed objective method are used for image quality evaluation with a set of images. The results show that the proposed EWPSNR based objective image quality evaluation method is more consistent with the subjective method than PSNR based one.
Keywords :
edge detection; geophysical signal processing; image classification; image reconstruction; remote sensing; edge distortion; edge weighted peak signal noise ratio; edge weighted remote sensing image quality evaluation method; human vision characteristics; image categorization; image reconstruction; mathematical calculation; objective image quality testing; subjective image quality testing; Computer science; Humans; Image coding; Image quality; Image reconstruction; PSNR; Pixel; Remote sensing; Software engineering; Testing; EWPSNR; image quality evaluation; remote sensing;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.179