Capture and transparency in coarse quantized images

Abstract

This study examines the effect of coarse quantization (blocking) on image recognition, and explores possible mechanisms. Thresholds for noise corruption showed that coarse quantization reduces drastically the recognizability of both faces and letters, well beyond the levels expected by equivalent blurring. Phase-shifting the spurious high frequencies introduced by the blocking (with an operation designed to leave both overall and local contrast unaffected, and feature localization) greatly improved recognizability of both faces and letters. For large phase shifts, the low spatial frequencies appear in transparency behind a grid structure of checks or lines. We also studied a more simple example of blocking, the checkerboard, that can be considered as a coarse quantized diagonal sinusoidal plaid. When one component of the plaid was contrast-inverted, it was seen in transparency against the checkerboard, while the other remained "captured" within the block structure. If the higher harmonics are then phase-shifted by pi, the contrast-reversed fundamental becomes captured and the other seen in transparency. Intermediate phase shifts of the higher harmonics cause intermediate effects, which we measured by adjusting the relative contrast of the fundamentals until neither orientation dominated. The contrast match varied considerably with the phase of the higher harmonics, over a range of about 1.5 log units. Simulations with the local energy model predicted qualitatively the results of the recognizability of both faces and letters, and quantitatively the apparent orientation of the modified checkerboard pattern. More generally, the model predicts the conditions under which an image will be "captured" by coarse quantization, or seen in transparency.

Hybrid motion illusions as examples of perceptual conflict

“…Our eyes and bodies are constantly in motion, and the image on the retina is therefore similar to taking a picture with an unsteady or moving camera; mid-level processes that accentuate objects share some commonalities with processes that decrease the effects of motion blur. In addition to Harmon and Julesz (1973), Oliva et al (2006), and Oliva and Schyns (2017), many investigators have examined the processes for integrating edge information or aligning phase information (for instance, Del Viva & Morrone, 1998;Henriksson, Hyvärinen, & Vanni, 2009;May & Georgeson, 2007;Morrone & Burr, 1997;Watt & Morgan, 1985). Such processes are most likely related to how the visual system adapts to blur (Elliott, Georgeson, & Webster, 2011;Webster, Georgeson, & Webster, 2002), and to processes that accentuate the presence of high spatial frequency edges even after the edges have visually disappeared (Brady & Oliva, 2012).…”

Seven challenges for image quality research

“…In the visual psychophysics literature, these two scenarios would fall under the aegis of capture and transparency, 38 which describe whether a target + background are perceived as one combined stimulus (captured), or whether they are perceived as two separate stimuli (transparent). In Ref.…”

Book Review: Perception of Pixelated Images

“…That portrait recognition improves when block shape is destroyed by noise instead suggests that the difficulty of recognizing quantized images is due to a competition between the integration of block and portrait shapes , at a higher visual processing stage than the early SF extraction stage (Bachmann and Kahusk, 1997 ; see also Caelli and Yuzyk, 1985 ). Besides the disruptive effect of the high SF block edges on perception, quantization was also reported to distort the second-order properties of the low SF image content (Caelli and Yuzyk, 1985 ; Bachmann and Kahusk, 1997 ; Morgan and Watt, 1997 ; Morrone and Burr, 1997 ). Although quantization was initially used to investigate the primary SF dependencies of human vision, this evidence shows that it also drastically distorts the higher-level (shape) properties of the image.…”