Marina Bloj

Perception of three-dimensional shape influences colour perception through mutual illumination.

Objects in the natural world possess different visual attributes, including shape, colour, surface texture and motion. Previous perceptual studies have assumed that the brain analyses the colour of a surface independently of its three-dimensional shape and viewing geometry, although there are neural connections between colour and two-dimensional form processing early in the visual pathway. Here we show that colour perception is strongly influenced by three-dimensional shape perception in a novel, chromatic version of the Mach Card—a concave folded card with one side made of magenta paper and the other of white paper. The light reflected from the magenta paper casts a pinkish glow on the white side. The perceived colour of the white side changes from pale pink to deep magenta when the perceived shape of the card flips from concave to convex. The effect demonstrates that the human visual system incorporates knowledge of mutual illumination—the physics of light reflection between surfaces—at an early stage in colour perception.

Measurements of the effect of surface slant on perceived lightness

When a planar object is rotated with respect to a directional light source, the reflected luminance changes. If surface lightness is to be a reliable guide to surface identity, observers must compensate for such changes. To the extent they do, observers are said to be lightness constant. We report data from a lightness matching task that assesses lightness constancy with respect to changes in object slant. On each trial, observers viewed an achromatic standard object and indicated the best match from a palette of 36 grayscale samples. The standard object and the palette were visible simultaneously within an experimental chamber. The chamber illumination was provided from above by a theater stage lamp. The standard objects were uniformly-painted flat cards. Different groups of naive observers made matches under two sets of instructions. In the Neutral Instructions, observers were asked to match the appearance of the standard and palette sample. In the Paint Instructions, observers were asked to choose the palette sample that was painted the same as the standard. Several broad conclusions may be drawn from the results. First, data for most observers were neither luminance matches nor lightness constant matches. Second, there were large and reliable individual differences. To characterize these, a constancy index was obtained for each observer by comparing how well the data were accounted for by both luminance matching and lightness constancy. The index could take on values between 0 (luminance matching) and 1 (lightness constancy). Individual observer indices ranged between 0.17 and 0.63 with mean 0.40 and median 0.40. An auxiliary slant-matching experiment rules out variation in perceived slant as the source of the individual variability. Third, the effect of instructions was small compared to the inter-observer variability. Implications of the data for models of lightness perception are discussed.

Optimal integration of shading and binocular disparity for depth perception.

We explore the relative utility of shape from shading and binocular disparity for depth perception. Ray-traced images either featured a smooth surface illuminated from above (shading-only) or were defined by small dots (disparity-only). Observers judged which of a pair of smoothly curved convex objects had most depth. The shading cue was around half as reliable as the rich disparity information for depth discrimination. Shading- and disparity-defined cues where combined by placing dots in the stimulus image, superimposed upon the shaded surface, resulting in veridical shading and binocular disparity. Independently varying the depth delivered by each channel allowed creation of conflicting disparity-defined and shading-defined depth. We manipulated the reliability of the disparity information by adding disparity noise. As noise levels in the disparity channel were increased, perceived depths and variances shifted toward those of the now more reliable shading cue. Several different models of cue combination were applied to the data. Perceived depths and variances were well predicted by a classic maximum likelihood estimator (MLE) model of cue integration, for all but one observer. We discuss the extent to which MLE is the most parsimonious model to account for observer performance.

An Equivalent Illuminant Model for the Effect of Surface Slant on Perceived Lightness

In the companion study (C. Ripamonti et al., 2004), we present data that measure the effect of surface slant on perceived lightness. Observers are neither perfectly lightness constant nor luminance matchers, and there is considerable individual variation in performance. This work develops a parametric model that accounts for how each observers lightness matches vary as a function of surface slant. The model is derived from consideration of an inverse optics calculation that could achieve constancy. The inverse optics calculation begins with parameters that describe the illumination geometry. If these parameters match those of the physical scene, the calculation achieves constancy. Deviations in the models parameters from those of the scene predict deviations from constancy. We used numerical search to fit the model to each observers data. The model accounts for the diverse range of results seen in the experimental data in a unified manner, and examination of its parameters allows interpretation of the data that goes beyond what is possible with the raw data alone.

Rendering complex scenes for psychophysics using RADIANCE: How accurate can you get?

Rendering packages are used by visual psychophysicists to produce complex stimuli for their experiments, tacitly assuming that the simulation results accurately reflect the light-surface interactions of a real scene. RADIANCE is a physically based, freely available, and commonly used rendering software. We validated the calculation accuracy of this package by comparing simulation results with measurements from real scenes. RADIANCE recovers color gradients well but the results are shifted in color space. Currently, there is no better simulation alternative for achieving physical accuracy than by combining a spectral rendering method with RADIANCE.

A framework for inverse tone mapping

In recent years many tone mapping operators (TMOs) have been presented in order to display high dynamic range images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The inverse of tone mapping, inverse tone mapping, expands a low dynamic range image (LDRI) into an HDRI. HDRIs contain a broader range of physical values that can be perceived by the human visual system. We propose a new framework that approximates a solution to this problem. Our framework uses importance sampling of light sources to find the areas considered to be of high luminance and subsequently applies density estimation to generate an expand map in order to extend the range in the high luminance areas using an inverse tone mapping operator. The majority of today’s media is stored in the low dynamic range. Inverse tone mapping operators (iTMOs) could thus potentially revive all of this content for use in high dynamic range display and image based lighting (IBL). Moreover, we show another application that benefits quick capture of HDRIs for use in IBL.

Real and predicted influence of image manipulations on eye movements during scene recognition

In this paper, we investigate how controlled changes to image properties and orientation affect eye movements for repeated viewings of images of natural scenes. We make changes to images by manipulating low-level image content (such as luminance or chromaticity) and/or inverting the image. We measure the effects of these manipulations on human scanpaths (the spatial and chronological path of fixations), additionally comparing these effects to those predicted by a widely used saliency model (L. Itti & C. Koch, 2000). Firstly we find that repeated viewing of a natural image does not significantly modify the previously known repeatability (S. A. Brandt & L. W. Stark, 1997; D. Noton & L. Stark, 1971) of scanpaths. Secondly we find that manipulating image features does not necessarily change the repeatability of scanpaths, but the removal of luminance information has a measurable effect. We also find that image inversion appears to affect scene perception and recognition and may alter fixation selection (although we only find an effect on scanpaths with the additional removal of luminance information). Additionally we confirm that visual saliency as defined by L. Itti and C. Kochs (2000) model is a poor predictor of real observer scanpaths and does not predict the small effects of our image manipulations on scanpaths.

An Empirical Study of the Traditional Mach Card Effect

The traditional achromatic Mach card effect is an example of lightness inconstancy and a demonstration of how shape and lightness perception interact. We present a quantitative study of this phenomenon and explore the conditions under which it occurs. The results demonstrate that observers show lightness constancy only when sufficient information is available about the light-source position, and the perceptual task required of them is surface identification rather than direct colour-appearance matching. An analysis and comparison of these results with the chromatic Mach card effect (Bloj et al 1999 Nature 402 877–879) demonstrate that the luminance effects of mutual illumination do not account for the change in lightness perception in the traditional Mach card.

A psychophysical evaluation of inverse tone mapping techniques

In recent years inverse tone mapping techniques have been proposed for enhancing low‐dynamic range (LDR) content for a high‐dynamic range (HDR) experience on HDR displays, and for image based lighting. In this paper, we present a psychophysical study to evaluate the performance of inverse (reverse) tone mapping algorithms. Some of these techniques are computationally expensive because they need to resolve quantization problems that can occur when expanding an LDR image. Even if they can be implemented efficiently on hardware, the computational cost can still be high. An alternative is to utilize less complex operators; although these may suffer in terms of accuracy. Our study investigates, firstly, if a high level of complexity is needed for inverse tone mapping and, secondly, if a correlation exists between image content and quality. Two main applications have been considered: visualization on an HDR monitor and image‐based lighting.

Dynamic range compression by differential zone mapping based on psychophysical experiments

In this paper we present a new technique for the display of High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as reference, that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO.