Title :
Image Quality Assessment: A Reduced Reference Algorithm for the Super-resolution Reconstruction Image
Author :
Yu Kang-Long ; Meng Zhao-kui ; Sun Ming-jie
Author_Institution :
Sch. of Instrum. Sci. & Optoelectron. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
Abstract :
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.
Keywords :
feature extraction; image reconstruction; image resolution; IQA methods; RRIQA method; SIFT; SSIM; image quality assessment methods; image size change; reduced reference algorithm; reduced-reference image quality assessment; scale invariant feature transform; structural similarity image metric; super-resolution reconstruction image; Computers; Feature extraction; Image quality; Image resolution; Interpolation; Quality assessment; Robustness; image quality assessment; imaging super-resolution reconstruction; scale invariant feature transform (SIFT); structural similarity image metric(SSIM);
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/IMCCC.2013.43
