Image Quality Assessment: a Reduced Reference Algorithm for the Super-resolution Reconstruction Image

被引：3
|
作者：
Yu Kang-Long [1 ]
Meng Zhao-Kui [1 ]
Sun Ming-Jie [1 ]
机构：
[1] Beijing Univ Aeronaut & Astronaut, Sch Instrument Sci & Optoelect Engn, Beijing 100191, Peoples R China
来源：
2013 THIRD INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2013年
关键词：
image quality assessment; imaging super-resolution reconstruction; structural similarity image metric(SSIM); scale invariant feature transform(SIFT);
D O I：
10.1109/IMCCC.2013.43
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The previous image quality assessment(IQA) methods request the same size of original and distorted image, not suitable for the super-resolution image. The effective of image size change has rarely been discussed. An improved reduced-reference image quality assessment (RRIQA) method based on the structural similarity image metric(SSIM) and scale invariant feature transform(SIFT) was put forward. The method is applicable to the super-resolution image, and considering more than one reference image. Experimental comparisons demonstrate the effectiveness of the proposed method.
引用
收藏
页码：171 / 175
页数：5
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