What makes an image appear to be a veridical representation of a real scene? Knowing what is necessary to produce a
"good" image also aids in the design of more efficient compression algorithms. We review our earlier work on video
compression and demonstrate the substantial savings and excellent image quality produced by spatial low-pass filtering
of most (but not all) of the individual frames. Currently, we work with still images. An example will show that simple
filtering can produce unexpected changes in the perceptual interpretation of a complex scene. I will describe and
demonstrate a new compression method we are developing based on the assumption that the fine structure in the
amplitude domain (and perhaps in phase, as well) can be of minimal importance in conveying the essence of a scene. We
find that a complex image can be reproduced surprisingly well by compressing the entire spatial frequency amplitude
spectrum to a very small number of terms.
Moving objects in films often appear normal or even sharper than they actually are, a phenomenon called motion sharpening. We sought to clarify which spatio-temporal frequency components of a moving image are sharpened when the pattern is moving. We applied various spatio-temporal filters to moving natural images and evaluated the perceived sharpness and smoothness of motion by comparing them to a stationary image. On each trial, subjects adjusted three parameters of the still image: overall luminance contrast, the slope of the amplitude function in the spatial frequency domain, and cut-off spatial frequency. We found the strongest motion sharpening when image frames were spatially band-reject filtered. In addition, spatially low-pass filtered movies induced stronger motion sharpening than spatially high-pass filtered movies. When temporal filters were applied, perceived sharpness became stronger when the movies were temporally low-pass filtered. A high-pass temporal filter drastically reduced the perceived quality of image motion. Our results demonstrate that the perceived contrast of higher spatial frequency components in moving images is enhanced by the interaction between different spatio-temporal frequency channels in the motion sharpening process. The results suggest that it is possible to compress and enhance moving images by removing higher spatio-temporal frequency information.
To understand the role of color in spatial vision, it is necessary to examine both the extent to which spatial discriminations can be based solely upon color differences and the interaction between color and luminance variations when they are simultaneously present. The well- known differences in the spatial and temporal contrast sensitivity functions for color and luminance and the apparently impoverished input from the color mechanisms to certain higher functions obscure the fact that spatial discriminations based solely upon color differences are quite good. For example, spatial frequency discriminations between high-contrast patterns at isoluminance are only slightly poorer than for comparable luminance patterns, averaging about 5% to 6% of the base frequency. Similarly, orientation differences of about 1 deg between isoluminant patterns can be reliably discriminated at high contrasts, even for stimuli that lie along a tritanopic confusion axis. Similar comparisons from several tasks are reviewed, as are tasks involving color-luminance interactions. These provide information about the target behavior that must ultimately be explained if the physiological basis of color vision is to be understood.