The implementation of automatic, adaptive filters in consumer imaging devices represents challenges to sharpness and resolution evaluation. The widely used e-SFR and other methods based on sine-waves and line targets are not necessarily representative of the capture of natural scene information. The recent dead leaves target is aimed at producing texture-MTFs that describe the capture of image detail under automatic non-linear, and contentaware processes. A newer approach to the texture-MTF measurement that substitutes the dead leaves target with pictorial images is presented in this paper. The aim of the proposed method is to measure effective-MTFs indicative of system characteristics for given scenes and camera processes. Nine pictorial images, portraying a variety of subjects and textures, were set as targets for a DSLR camera and a high-end smartphone camera. Computed MTFs were found to be congruent with the dead leaves MTF. Scene dependency was reported mainly for the smartphone camera measurements, providing insight into the performance of the content-dependent processes. Results from the DLSR camera images, captured with minimum non-adaptive operations, were reasonably consistent for the majority of the scenes. Based on variations in scene-dependent MTFs, we make recommendations for scene content that is best for texture-MTF analysis.
Riccardo Branca, Sophie Triantaphillidou, Peter Burns, "Texture MTF from images of natural scenes" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XIV, 2017, pp 113 - 120, https://doi.org/10.2352/ISSN.2470-1173.2017.12.IQSP-255