Imagine watching a severely out-of-focus printed photograph, holding it at arm's length with image blur greatly reducing the details that can be recognized. If you now tack the photograph to the wall and step back to watch it from a moderate distance, say a couple of meters, the blur due to defocus may still be the limiting factor for recognizing details. Nevertheless, many people would agree that the blur is less disturbing now, and the picture seems to be more detailed than before. In the age of digital photography, it is easily possible to observe the effect on a computer screen by resizing the image, which shows that the effect does not depend on varying the distance at which a photograph is seen, but rather on the visual angle spanned. In the present study we aimed at confirming and quantifying these cursory findings under laboratory conditions.
Subsequently, we will use the terms “subjective detailedness” and “objective detailedness” to denote the subject's perception and the physical stimulus properties, respectively. A rating of subjective detailedness is not obtained by counting individual stimulus elements, but rather reflects a spontaneous overall impression. Objective detailedness in natural images can be controlled by a spatial low-pass filter.
The phenomenon investigated here is not the only case where a subjective increase in image quality is perceived without any information added to the image. A well-known example is the mosaic effect (Harmon & Julesz,
1973), where pictures are assembled from large homogenous blocks. There, blurring the image (or watching it from a far enough distance) removes the influence of the block boundaries and facilitates the recognition of the picture content. As opposed to these effects, the phenomenon investigated in the present study only depends on the image scaling, but not on the change of any image content.
Subjective detailedness may be seen as a facet of subjective image quality. The latter is frequently assessed in photography and imaging science and can be measured subjectively or objectively (Nilsson,
1999). It has been proposed to describe image quality on three levels, namely image quality metrics, image quality attributes, and image preference (e.g., Dalal, Rasmussen, Nakaya, Crean, & Sato,
1998; Natale-Hoffman, Dalal, Rasmussen, & Sato,
1999). Image quality metrics are primarily simple physical measures (such as line density), though they may be scaled to account for human perception. Image preference is a subjective rating of like or dislike, usually on a one-dimensional scale. Image quality attributes describe an intermediate level of image quality, such as overall line quality, combining both subjective and objective characteristics.
Turning from imaging science to vision science, one may wish to devise a visuo-cognitive scheme of image quality measures. In addition to a physical level of description, an intermediate level would account for the properties of the human visual system while being largely agnostic to the meaning of the image content. Subjective detailedness, together with other measures, would be a candidate for such an intermediate descriptor. The top level of image quality measures would describe how well objects or other meaningful image features can be detected or recognized. The relationship between the lowest and the highest level of description is subject to many investigations, for instance in the field of radiology (van Overveld,
1995). Ultimately, one may envisage rules that transform one level of description into a different level through mathematical coordinate transformation. Such a conversion has already been successfully demonstrated in some specific cases (e.g., Martens,
2002; Martens & Kayargadde,
1996).
A question germane to the present one was investigated by Barten (
1989), who assessed subjective ratings of image quality and found that there is an optimal display size (or optimal viewing distance) for a given number of pixels. The optimal conditions can be computed with the aid of an equation that takes into account the modulation transfer functions of the eye and of the display device. The subjective rating of image quality is inherently difficult, not only because it usually involves the attempt to map a multifactorial problem onto a one-dimensional scale, but also because there is a sizable interindividual variability. Even with blur alone, subjects differ considerably regarding their threshold for perceiving the image degradation (Layton, Dickinson, & Pluznick,
1978).
A number of further studies have investigated aspects of vision that are related to the present question. Field and Brady (
1997) and Tolhurst and Tadmor (
1997), among others, have assessed the perception of blur in different contexts, aiming at a better understanding of the mechanisms underlying perception, and Schieber (
1994) measured the blur tolerance to optimize the legibility of highway signs. These studies, however, do not predict subjective detailedness. Similarly, previous studies by, for instance, Nothdurft (
1985), Joseph, Victor, and Optican (
1997), Kingdom and Keeble (
1999), and Rainville and Kingdom (
2002) reveal important characteristics of the scale invariance of specific perceptual tasks, such as texture segregation and the perception of spatial correlation, without providing a basis for the prediction of subjective detailedness. Interestingly, though, Parish and Sperling (
1991) did not find an effect of viewing distance, i.e., retinal size, on the discrimination of letters that were spatially filtered and had noise added.
In a thorough series of investigations, Vicario (
1971a,
1971b,
1972) and Masin (
1980) found that a grating covering a small stimulus area can be perceived clearly and in full at a shorter distance than a grating of identical spatial frequency covering a larger stimulus area, and that the density of the grating appears lower in the small stimulus. This finding predicts that a small stimulus should appear less detailed than a large stimulus. Another related area of visual performance is the perception of numerosity, which has recently gained renewed interest, and which been proposed as an independent primary visual property (Burr & Ross,
2008, but see also Durgin,
2008). Already Ponzo (
1928) demonstrated with a series of visual illusions that perceived numerosity may depend on a variety of geometrical factors including the size of the stimulus. For instance, he showed that a small spoke wheel appears to have more spokes than a large spoke wheel, despite the number of spokes objectively being the same. Although in this case the direction of the effect indeed seems to support our prediction of a higher subjective detailedness in small stimuli, the results of experiments on numerosity cannot necessarily be transferred to the question of detailedness of natural stimuli as those usually contain a small number of main elements (a few people, some houses, or similar) which would not be perceived as changing in number even when detailedness changes.
In summary, the idea that subjective detailedness differs from objective detailedness is hinted at in previous work, but it needs to be assessed whether it is a substantial and robust phenomenon. This, and a first explanatory attempt, is the aim of the present report.