Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1907-1914, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1907-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1907-1914, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1907-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

IMAGE QUALITY ASSESSMENT OF HIGH-RESOLUTION SATELLITE IMAGES WITH MTF-BASED FUZZY COMPREHENSIVE EVALUATION METHOD

Z. Wu, Z. Luo, Y. Zhang, F. Guo, and L. He Z. Wu et al.
  • School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

Keywords: Image Quality Assessment, High-resolution Satellite Images, MTF, Fuzzy Comprehensive Evaluation

Abstract. A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.