Image Reconstruction using its Spatial and Geometrical Information


Authors : K. B. Ranushka Pasindu Dharmaranga; Ligitha Sakthymayuran

Volume/Issue : Volume 7 - 2022, Issue 5 - May

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3NBzadh

DOI : https://doi.org/10.5281/zenodo.6787485

Image reconstruction is currently often used in a wide range of technological and medical applications. The local image feature descriptor is the most critical factor influencing the performance of object reconstruction or image retrieval systems. This study provides and demonstrates a strategy for replicating images. In this approach, Training photos are used to extract local feature descriptors; at first images are recreated using local feature descriptors and geometric information. Scale invariant feature transform (SIFT) descriptors are used to characterize images, and the feature extraction method is similar to how descriptors are used in the training phase. The unknown image closest neighbor descriptor built by using pairwise matching. For each of the regions of interest, visually equivalent patches may be in the external image database.To detect patch overlapping regions between the new patch and the patch already present in the query image, the Mean Squared Error (MSE) is used. To eliminate overlapping patches, the highest MSE threshold value is chosen as the default threshold (DT) in this experimental technique. Based on the experimental results, an image may be approximated and rebuilt using image local feature descriptors.

Keywords : Image reconstruction, image retrieval, image feature descriptor, geometric information, partial information.

CALL FOR PAPERS


Paper Submission Last Date
31 - March - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe