No-reference remote sensing image quality assessment using a comprehensive evaluation factor

Lin Wang; Xu Wang; Xiao Li; Xiaopeng Shao

doi:10.1117/12.2053293

22 May 2014 No-reference remote sensing image quality assessment using a comprehensive evaluation factor

Lin Wang, Xu Wang, Xiao Li, Xiaopeng Shao

Proceedings Volume 9124, Satellite Data Compression, Communications, and Processing X; 912414 (2014) https://doi.org/10.1117/12.2053293
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

The conventional image quality assessment algorithm, such as Peak Signal to Noise Ratio （PSNR）， Mean Square Error（MSE） and structural similarity (SSIM), needs the original image as a reference. It’s not applicable to the remote sensing image for which the original image cannot be assumed to be available. In this paper, a No-reference Image Quality Assessment (NRIQA) algorithm is presented to evaluate the quality of remote sensing image. Since blur and noise (including the stripe noise) are the common distortion factors affecting remote sensing image quality, a comprehensive evaluation factor is modeled to assess the blur and noise by analyzing the image visual properties for different incentives combined with SSIM based on human visual system (HVS), and also to assess the stripe noise by using Phase Congruency (PC). The experiment results show this algorithm is an accurate and reliable method for Remote Sensing Image Quality Assessment.

Citation Download Citation

Lin Wang, Xu Wang, Xiao Li, and Xiaopeng Shao "No-reference remote sensing image quality assessment using a comprehensive evaluation factor", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 912414 (22 May 2014); https://doi.org/10.1117/12.2053293

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