A Dynamic Data Driven and Data Segregation Approach Image Restoration Using Neural Networks

Authors

  • A. Gnanasekar
  • S. Selvi
  • A.S.U. Soundharyaa
  • A. Malini
  • K.R. Ramya

DOI:

https://doi.org/10.47059/revistageintec.v11i2.1718

Abstract

Image restoration is the method of restoring an image to its original state by removing noise and blur. Image disclarity is crucial to maintain in a variety of cases, including photography, where motion blur is caused by camera shake when taking images, radar imaging, where the impact of image system reaction is removed, and so on. Image noise is an unwanted signal that appears in an image from a sensor, such as a power / energy signal, or from the atmosphere, such as rain or snow. Coding artefacts, resolution limitations, transmission noise, object motion, camera shake, or a confluence of events could cause image degradation. With the intention of separating HF and LF objects, image decomposition is used to decompose the distorted image into a pattern layer (High Frequency Component) and a framework layer (Low Frequency Component).

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Published

2021-06-02

Issue

Section

Articles