Title :
Enhanced image quality evaluation based on SIFT feature
Author :
Guang-Lei Wen ; Gang Liu ; Si-Guo Zheng ; Shang-Kun Ning
Author_Institution :
Coll. of Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
Abstract :
In the study of Retinex image enhancement methods, there is a need to determine the quality of the image enhancement. But the images obtained through different Retinex image enhancement methods were quite similar. Thus, subjective evaluation criteria are not reliable. In this paper, the SIFT feature points are presented as an objective evaluation of images. Image quality evaluation method based on SIFT features were turned out to be feasible. Experimental results are consistent with the conclusions drawn by synthesizing information entropy, standard deviation, and the mean squared error.
Keywords :
Gaussian processes; image enhancement; transforms; Retinex image enhancement methods; SIFT feature; image quality evaluation enhancement; information entropy synthesis; mean square error; objective evaluation; standard deviation; Abstracts; Entropy; Image recognition; Image restoration; Reliability; Standards; Enhanced image; Feature; Image quality evaluate; Retinex; SIFT (Scale Invariant Feature Transform);
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
Print_ISBN :
978-1-4799-4216-9
DOI :
10.1109/ICMLC.2014.7009120