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公开(公告)号：US10964076B2
公开(公告)日：2021-03-30
申请号：US16504196
申请日：2019-07-05
Applicant: Tata Consultancy Services Limited
Inventor： Jayavardhana Rama Gubbi Lakshminarasimha , Karthik Seemakurthy , Sandeep Nk , Ashley Varghese , Shailesh Shankar Deshpande , Mariaswamy Girish Chandra , Balamuralidhar Purushothaman , Angshul Majumdar
Abstract: This disclosure relates generally to image processing, and more particularly to method and system for image reconstruction using deep dictionary learning (DDL). The system collects the degraded image as test image and processes the test image to extract sparse features from the test image, at different levels, using dictionaries. The extracted sparse features and data from the dictionaries are used by the system to reconstruct the HR image corresponding to the test image.
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公开(公告)号：US10679098B2
公开(公告)日：2020-06-09
申请号：US15902079
申请日：2018-02-22
Applicant: Tata Consultancy Services Limited
Inventor： Jayavardhana Rama Gubbi Lakshminarasimha , Akshaya Ramaswamy , Sandeep Nellyam Kunnath , Ashley Varghese , Balamuralidhar Purushothaman
Abstract: The disclosure herein generally relate to scene change detection, and, more particularly, to use of Unmanned Vehicle (UV) to inspect a scene and perform a scene change detection using UVs. When a UV performs visual inspection of an area or an object, due to various factors, such as but not limited to environmental factors, and movement of object and/or the UV, image of the area/object captured by the drone lacks clarity, which in turn makes detection of any object a difficult task. The UV disclosed herein uses a multi scale super pixel technique for visual change detection, in order to solve the aforementioned issues. In an embodiment, the UV captures an image, identifies a reference image that matches the captured image, and generates a change map. The multi-scale super pixel analysis is then performed on this change map to detect changes between the captured image and the reference image.
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