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.
The standard imaging lens for a high resolution sensor was modified to achieve the extended depth of field (EDoF) from
300 mm to infinity. In the module the raw sensor outputs are digitally processed to obtain high contrast images. The
overall module is considered as an integrated computational imaging system (ICIS). The simulation results for
illustrative designs with different amount of spherical aberrations are provided and compared. Based on the results of
simulations we introduced the limiting value of the PSF Strehl ratio as the integral threshold criteria to be used during
EDoF lens optimization. A four-element standard lens was modified within the design constraints to achieve the EDoF
performance. Two EDoF designs created with different design methods are presented. The imaging modules were
compared in terms of Strehl ratios, limiting resolution, modulation frequencies at 50% contrast, and SNR. The output
images were simulated for EDoF modules, passed through the image processing pipeline, and compared against the
images obtained with the standard lens module.
An accurate measurement of the point spread function (PSF) for the extended depth of field (EDoF) cell phone camera
with CMOS sensor is very important for image processing and image restoration. But due to the coarse sampling of the
PSF by CMOS sensor, the overall system including the imaging subsystem and sampling subsystem is a shift-variant
system with respect to the sample-scene phase parameter within sub-pixel range. In this paper, we present the sub-pixel
digital algorithm to estimate the overall camera PSF based on the measurement of a high resolution PSF of the imaging
lens. The sub-pixel digital algorithm averages the shifted high resolution PSFs of the lens over one active pixel area
with the assumption of uniform random distribution of point source location within one active pixel area. Then the
averaged high resolution PSF is down sampled onto Bayer plane to obtain the shift-invariant overall system PSF. We
applied this shift-invariant PSF for image restoration of blurred images captured with an extended depth of field camera.
The processed images are compared with originally captured images. Improvement of image quality is seen.
We present a technique for converting continuous gray-scale images to halftone (black and white) images that lend themselves to lossless data compression with compression factor of three or better.
Our method involves using novel halftone mask structures which consist of non-repeated threshold values. We have versions of both dispersed-dot and clustered-dot masks, which produce acceptable images for a variety of printers.
Using the masks as a sort key allows us to reversibly rearrange the image pixels and partition them into groups with a highly skewed distribution allowing Huffman compression coding techniques to be applied. This gives compression ratios in the range 3:1 to 10:1.