The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 07, 2019

Filed:

Sep. 22, 2017
Applicant:

Wipro Limited, Bangalore, IN;

Inventors:

Sethuraman Ulaganathan, Tiruchirapalli, IN;

Manjunath Ramachandra, Bangalore, IN;

Prasanna Hegde, Uttara Kannada, IN;

Assignee:

Wipro Limited, Bangalore, IN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/00 (2006.01); G06T 5/50 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06T 5/005 (2013.01); G06T 5/50 (2013.01); G06T 7/001 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Systems and methods for removing rain streak distortion from a distorted video are described. The system receives sample non-distorted images and sample distorted images of a video. The sample non-distorted images are indicative of non-raining condition and the sample distorted images are indicative of raining condition in the video. The system further determines first temporal information from the sample distorted images and second temporal information from the sample non-distorted images. The first temporal information indicative of a change in the rain streak distortion pattern and the second temporal information indicative of a change in a non-rain streak distortion pattern. Further, the system correlates the first temporal information with the second temporal information to generate a training model comprising one or more trained weights. Further, the system removes the rain streak distortion from a real-time distorted video by applying the training model, which results in the generation of the non-distorted video.


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