An observer study was run to determine the detection thresholds of several representative examples of column fixed
pattern noise, in the presence of varying levels of shot noise, which is known to mask structured noise. The data obtained
were fit well at relevant shot noise levels by a simple model based on signal detection theory. Individual metrics of fixed
pattern noise and shot noise, used in the masking equation, were computed from one dimensional integrations involving
the capture noise power spectra (mapped to CIELAB space); the modulation transfer function of the display; the display
pixel pitch; the viewing distance; and the S-CIELAB luminance contrast sensitivity function. The results of this work
can be used to predict detection thresholds that can be added to photon transfer curves for the purpose of determining
whether fixed pattern noise will be visible.
Image sensor crosstalk can be divided into spectral crosstalk and pixel crosstalk. This paper focuses on the pixel
crosstalk and its effect on signal to noise ratio (SNR). Pixel crosstalk occurs in the spatial domain and is due to
the signal leakage between adjacent pixels either by imperfect optical isolation or diffusion of electrons. This will
have a negative impact on image quality mainly in two ways: spatial blurring and decreased SNR due to more
aggressive color correction required. A method for modeling the spectral broadening due to the pixel crosstalk
is used where a matrix is calculated from crosstalk kernels representing the spatial leakage between neighboring
pixels. In order to quantify the amount of crosstalk we present a method in which ratios of integrals of the same
color channel but within different wavelength intervals are calculated. This provides a metric that is more robust
with respect to color channel scaling. To study the impact on SNR due to pixel crosstalk, a number of SNR
metrics are compared to results from a limited psychophysical study. The studied SNR metrics are the metric
used for calculating the SNR10 value in mobile imaging, the ISO 12232 noise metric and a metric where the
signal is transformed into orthogonal color opponent channels, thereby enabling the analysis of the luminance
noise separate from the chrominance noises. The results indicate that the ISO total noise and SNR10 metric
yield very similar results and that the green channel has the largest individual impact on the crosstalk.
Smooth pursuit eye movements align the retina with moving targets, ideally stabilizing the retinal image. At a steadystate,
eye movements typically reach an approximately constant velocity which depends on, and is usually lower than the
target velocity. Experiment 1 investigated the effect of target size and velocity on smooth pursuit induced by realistic
images (color photographs of an apple and flower subtending 2° and 17°, respectively), in comparison with a small dot
subtending a fraction of a degree. The extended stimuli were found to enhance smooth pursuit gain. Experiment 2
examined the absolute velocity limit of smooth pursuit elicited by the small dot and the effect of the extended targets on
the velocity limit. The eye velocity for tracking the dot was found to be saturated at about 63 deg/sec while the saturation
velocity occurred at higher velocities for the extended images. The difference in gain due to target size was significant
between dot and the two extended stimuli, while no statistical difference exists between an apple and flower stimuli of
wider angular extent. Detailed knowledge of the smooth pursuit eye movements is important for several areas of
electronic imaging, in particular, assessing perceived motion blur of displayed objects.
Viewing video on mobile devices is becoming increasingly common. The small field-of-view and the vibrations in
common commuting environments present challenges (hardware and software) for the imaging community. By
monitoring the vibration of the display, it could be possible to stabilize an image on the display by shifting a portion of a
large image with the display (a field-of-view expansion approach). However, the image should not be shifted exactly per
display motion because eye movements have a 'self-adjustment' ability to partially or completely compensate for
external motions that can make a perfect compensation appear to overshoot. In this work, accelerometers were used to
measure the motion of a range of vehicles, and observers' heads and hands as they rode in those vehicles to support the
development of display motion compensation algorithms.
Conference Committee Involvement (4)
Digital Photography X
3 February 2014 | San Francisco, California, United States
Digital Photography IX
4 February 2013 | Burlingame, California, United States
Digital Photography VIII
23 January 2012 | Burlingame, California, United States
Digital Photography VII
24 January 2011 | San Francisco Airport, California, United States
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