Showing papers by "Brian A. Wandell published in 2002"

Functional measurements of human ventral occipital cortex: retinotopy and colour.

Abstract: Human colour vision originates in the cone photoreceptors, whose spatial density peaks in the fovea and declines rapidly into the periphery. For this reason, one expects to find a large representation of the cone–rich fovea in those cortical locations that support colour perception. Human occipital cortex contains several distinct foveal representations including at least two that extend onto the ventral surface: a region thought to be critical for colour vision. To learn more about these ventral signals, we used functional magnetic resonance imaging to identify visual field maps and colour responsivity on the ventral surface. We found a visual map of the complete contralateral hemifield in a 4 cm2 region adjacent to ventral V3; the foveal representation of this map is confluent with that of areas V1/2/3. Additionally, a distinct foveal representation is present on the ventral surface situated 3–5 cm anterior from the confluent V1/2/3 foveal representations. This organization is not consistent with the definition of area V8, which assumes the presence of a quarter field representation adjacent to V3v. Comparisons of responses to luminance–matched coloured and achromatic patterns show increased activity to the coloured stimuli beginning in area V1 and extending through the new hemifield representation and further anterior in the ventral occipital lobe.

Visual Areas in Macaque Cortex Measured Using Functional Magnetic Resonance Imaging

Abstract: We describe the first systematic functional magnetic resonance imaging (fMRI) measurements of visual field maps in macaque visual cortex. The boundaries of visual areas V1, V2, V3, V3A, V4, MT/V5, and TEO/V4A were identified using stimuli that create traveling waves of activity in retinotopically organized areas of the visual cortex. Furthermore, these stimuli were used to measure the dimensions of the representations of the central 11° in V1–V3, quantitative visual field eccentricity functions for V1–V3 and MT, and the distribution of foveal and peripheral signals within the occipital lobe. Within areas V1, V2, MT, and portions of V4, the fMRI signals were 5–10 times the noise level (3 mm3 volumes of interest). Signals were weaker but still significant in other cortical regions, including V3, V3A, and TEO. There is good agreement between the fMRI maps and the visual area maps discovered using local anatomical and physiological measurements. The fMRI measurements allow one to obtain a broad view of the distribution of cortical signals, spanning multiple visual areas at a single point in time. The combination of scale and sensitivity demonstrated here create a good foundation for measuring how localized signals and lesions influence the responses and reorganization in widely separated cortical regions. The ability to measure human and macaque maps using the same technology will make it possible to define computational homologies between the two species.

Reorganization of human cortical maps caused by inherited photoreceptor abnormalities

Abstract: We describe a compelling demonstration of large-scale developmental reorganization in the human visual pathways. The developmental reorganization was observed in rod monochromats, a rare group of congenitally colorblind individuals who virtually lack cone photoreceptor function. Normal controls had a cortical region, spanning several square centimeters, that responded to signals initiated in the all-cone foveola but was inactive under rod viewing conditions; in rod monochromats this cortical region responded powerfully to rod-initiated signals. The measurements trace a causal pathway that begins with a genetic anomaly that directly influences sensory cells and ultimately results in a substantial central reorganization.

Optical efficiency of image sensor pixels

Abstract: The ability to reproduce a high-quality image depends strongly on the image sensor light sensitivity. This sensitivity depends, in turn, on the materials, the circuitry, and the optical properties of the pixel. We calculate the optical efficiency of a complementary metal oxide semiconductor (CMOS) image sensor pixel by using a geometrical-optics phase-space approach. We compare the theoretical predictions with measurements made by using a CMOS digital pixel sensor, and we find them to be in agreement within 3%. Finally, we show how to use these optical efficiency calculations to trade off image sensor pixel sensitivity and functionality as CMOS process technology scales.

High Dynamic Range Imaging of Natural Scenes.

Abstract: The ability to capture and render high dynamic range scenes limits the quality of current consumer and professional digital cameras. The absence of a well-calibrated high dynamic range color image database of natural scenes is an impediment to developing such rendering algorithms for digital photography. This paper describes our efforts to create such a database. First, we discuss how the image dynamic range is affected by three main components in the imaging pipeline: the optics, the sensor and the color transformation. Second, we describe a calibrated, portable high dynamic range imaging system. Third, we discuss the general properties of seventy calibrated high dynamic range images of natural scenes in the database (http://pdc.stanford.edu/hdri/). We recorded the calibrated RGB values and the spectral power distribution of illumination at different locations for each scene. The scene luminance ranges span two to six orders of magnitude. Within any scene, both the absolute level and the spectral composition of the illumination vary considerably. This suggests that future high dynamic range rendering algorithms need to account jointly for local color adaptation and local illumination level.

Natural scene-illuminant estimation using the sensor correlation

Abstract: This paper describes practical algorithms and experimental results concerning illuminant classification. Specifically, we review the sensor correlation algorithm for illuminant classification and we discuss four changes that improve the algorithm's estimation accuracy and broaden its applicability. First, we space the classification illuminants evenly along the reciprocal scale of color temperature, called "mired," rather than the original color-temperature scale. This improves the perceptual uniformity of the illuminant classification set. Second, we calculate correlation values between the image color gamut and the reference illuminant gamut, rather than between the image pixels and the illuminant gamuts. This change makes the algorithm more reliable. Third, we introduce a new image scaling operation to adjust for overall intensity differences between images. Fourth, we develop the three-dimensional classification algorithms using all three-color channels and compare this with the original two algorithms from the viewpoint of accuracy and computational efficiency. The image processing algorithms incorporating these changes are evaluated using a real image database with calibrated scene illuminants.

Common principles of image acquisition systems and biological vision

Abstract: In this paper we argue that biological vision and electronic image acquisition share common principles despite their vastly different implementations. These shared principles are based on the need to acquire a common set of input stimuli as well as the need to generalize from the acquired images. Two related principles are discussed in detail, namely, multiple parallel image representations and the use of dedicated local memory in various stages of acquisition and processing. We review relevant literature in visual neuroscience and image systems engineering to support our argument. Particularly, the paper discusses multiple capture image acquisition, with applications such as dynamic range, field-of-view, or depth-of-field extension. Finally, as an example, a novel multiple-capture-single-image complementary metal-oxide-semiconductor sensor is presented. This sensor illustrates the principles that are shared among biological vision and image acquisition.

Chromatic light adaptation measured using functional magnetic resonance imaging.

Abstract: Sensitivity changes, beginning at the first stages of visual transduction, permit neurons with modest dynamic range to respond to contrast variations across an enormous range of mean illumination. We have used functional magnetic resonance imaging (fMRI) to investigate how these sensitivity changes are controlled within the visual pathways. We measured responses in human visual area V1 to a constant-amplitude, contrast-reversing probe presented on a range of mean backgrounds. We found that signals from probes initiated in the L and M cones were affected by backgrounds that changed the mean absorption rates in the L and M cones, but not by background changes seen only by the S cones. Similarly, signals from S cone-initiated probes were altered by background changes in the S cones, but not by background changes in the L and M cones. Performance in psychophysical tests under similar conditions closely mirrored the changes in V1 fMRI signals. We compare our data with simulations of the visual pathway from photon catch rates to cortical blood-oxygen level-dependent signals and show that the quantitative fMRI signals are consistent with a simple model of mean-field adaptation based on Naka-Rushton (Naka and Rushton, 1966) adaptation mechanisms within cone photoreceptor classes.

Experimental high speed CMOS image sensor system and applications

Abstract: CMOS image sensors are capable of very high-speed non-destructive readout, enabling many novel applications. To explore such applications, we designed and prototyped an experimental high speed imaging system based on a CMOS digital pixel sensor (DPS). The experimental system comprises a PCB that has the DPS chip interfaced to a PC via three I/O cards supported by an easy to use software environment. The system is capable of image acquisition at rates of up to 1,400 frames/sec. After describing the DPS chip and experimental imaging system,we present two applications: dynamic range extension and optical flow estimation. These applications rely on the DPS's ability to perform non-destructive readout of multiple frames at high-speed.

Illuminant Estimation of Natural Scene Using the Sensor Correlation Method

Abstract: several likely types. The classification approach rather than the estimation approach is simple for data processing, stable forcomputation, and appropriate for applications such as photography. In a previous paper [1], we built on earlier illuminantclassification methods [2] to estimate the illuminant color temperature. Our illuminant classification was to restrict theestimation to a set of blackbody radiators. Color temperature classification provides simple specification of many common