A number of research groups have employed radial frequency patterns (Wilkinson, Wilson, & Habak,
1998) to study the perception of periodic structure in experimental images. Complex-shaped closed figures can be synthesized from the sum of a set of simple radial frequency patterns of differing cyclical period, amplitude and phase. Adaptation (Anderson, Habak, Wilkinson, & Wilson,
2007; Bell, Wilkinson, Wilson, Loffler, & Badcock,
2009), masking (Bell, Badcock, Wilson, & Wilkinson,
2007) and sub-threshold summation (Bell & Badcock,
2009) studies suggest that the perception of spatial structure in these patterns is based on the outputs of a set of channels, each of which is selective for a narrow range of radial modulation frequencies. In this paper, visual sensitivity to spatial distortions in natural scenes was examined systematically. Image distortions were introduced into natural scenes with a pixel-remapping algorithm in which the positions of pixels in an undistorted source image were remapped to new locations in a distorted target image, with linear interpolation between pixels. The transform that controls the pixel shifts is represented as a pair of 2D images whose pixel-by-pixel values represent the spatial shift of each source image pixel. One image contains the horizontal shift of each pixel, the second independent image contains the vertical pixel shifts. The transform images have zero mean so that there is no shift in the overall position of the image. This method allows the application of Fourier analysis (Bracewell,
1969) to represent any distortion transform into the linear sum of a set of periodic distortions of differing scale, amplitude and phase and extends studies of radial frequency patterns to real scenes. Based this deconstruction and reconstruction analysis, sensitivity to distortions at different spatial periods was examined. This approach is in direct analogy to the techniques used to analyze sensitivity to spatial structure in complex images (Bex, Mareschal, & Dakin,
2007; Bex & Makous,
2001; Bex, Solomon, & Dakin,
2009) and to identify channels for spatial variation in luminance contrast (Campbell & Robson,
1968) and contour structure (Wilkinson et al.,
1998) in the visual system.