Dr. Tripurari Singh Profile

Dr. Tripurari Singh

Engineer at Image Algorithmics

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 24 January 2012 Paper

Joint chromatic aberration correction and demosaicking

Mritunjay Singh, Tripurari Singh

Proceedings Volume 8299, 82990D (2012) https://doi.org/10.1117/12.908837

KEYWORDS: Chromatic aberrations, Optical filters, Cameras, Image processing, Space operations, Algorithm development, Numerical stability, Lenses, Optical resolution, Linear filtering

Read Abstract +

Chromatic Aberration of lenses is becoming increasingly visible with the rise of sensor resolution, and methods to algorithmically correct it are becoming increasingly common in commercial systems. A popular class of algorithms undo the geometric distortions after demosaicking. Since most demosaickers require high frequency correlation of primary colors to work effectively, the result is artifact-ridden as Chromatic Aberration destroys this correlation. The other existing approach of undistorting primary color images before demosaicking requires resampling of sub-sampled primary color images and is prone to aliasing. Furthermore, this algorithm cannot be applied to panchromatic CFAs. We propose a joint demosaicking and Chromatic Aberration correction algorithm that is applicable to both panchromatic and primary color CFAs and suffers from none of the above problems. Our algorithm treats the mosaicing process as a linear transform that is invertible if luminance and chrominance are appropriately bandlimited. We develop and incorporate Chromatic Aberration corrections to this model of the mosaicing process without altering its linearity or invertibility. This correction works for both space variant linear filter demosaicking and the more aggressive compressive sensing reconstruction.

Proceedings Article | 24 January 2011 Paper

Rectangular pixels for efficient color image sampling

Tripurari Singh, Mritunjay Singh

Proceedings Volume 7876, 78760V (2011) https://doi.org/10.1117/12.872248

KEYWORDS: Optical filters, Modulation, Sensors, Nonlinear filtering, Image filtering, Image resolution, Linear filtering, Cameras, Image quality, Video

Read Abstract +

We present CFA designs that faithfully capture images with specified luminance and chrominance bandwidths. Previous academic research has mostly been concerned with maximizing PSNR of reconstructed images without regard to chrominance bandwidth and cross-talk. Commercial systems, on the other hand, pay close attention to both these parameters as well as to the visual quality of reconstructed images. They commonly sacrifice resolution by using a sufficiently aggressive OLPF to achieve low cross-talk and artifact free images. In this paper, we present the so called Chrominance Bandwidth Ratio, r, model in an attempt to capture both the chrominance bandwidth and the cross-talk between the various signals. Next, we examine the effect of tuning photosite aspect ratio, a hitherto neglected design parameter, and show the benefit of setting it at a different value than the pixel aspect ratio of the display. We derive panchromatic CFA patterns that provably minimize the photo-site count for all values of r. An interesting outcome is a CFA design that captures full chrominance bandwidth, yet uses fewer photosites than the venerable color-stripe design. Another interesting outcome is a low cost practical CFA design that captures chrominance at half the resolution of luminance using only 4 unique filter colors, that lends itself to efficient linear demosaicking, and yet vastly outperforms the Bayer CFA with identical number of photosites demosaicked with state of the art compute-intensive nonlinear algorithms.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years