Welcome to the InfoSci Platform
Reference Hub1
The Fundamentals of Medical Image Restoration

The Fundamentals of Medical Image Restoration

Kirti Raj Bhatele, Devanshu Tiwari
Copyright: © 2019 |Pages: 19
ISBN13: 9781522558767|ISBN10: 1522558764|EISBN13: 9781522558774
DOI: 10.4018/978-1-5225-5876-7.ch004
Cite Chapter Cite Chapter

MLA

Bhatele, Kirti Raj, and Devanshu Tiwari. "The Fundamentals of Medical Image Restoration." Medical Image Processing for Improved Clinical Diagnosis, edited by A. Swarnambiga, IGI Global, 2019, pp. 81-99. https://doi.org/10.4018/978-1-5225-5876-7.ch004

APA

Bhatele, K. R. & Tiwari, D. (2019). The Fundamentals of Medical Image Restoration. In A. Swarnambiga (Ed.), Medical Image Processing for Improved Clinical Diagnosis (pp. 81-99). IGI Global. https://doi.org/10.4018/978-1-5225-5876-7.ch004

Chicago

Bhatele, Kirti Raj, and Devanshu Tiwari. "The Fundamentals of Medical Image Restoration." In Medical Image Processing for Improved Clinical Diagnosis, edited by A. Swarnambiga, 81-99. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-5876-7.ch004

Export Reference

Mendeley
Favorite

Abstract

This chapter simply encapsulates the basics of image restoration, various noise models, and degradation model including some blur and image restoration filters. The mining of high resolution information from the low-resolution images is a very vital task in several applications of digital image processing. In recent times, a lot of research work has been carried out in this field in order to improve the resolution of real medical images especially when the given images are corrupted with some kind of noise. The displayed images are the result of the various stages that might cause imperfections in the digital images, for instance the so-called imaging and capturing process can itself degrade the original scene. The imperfections present in the image need to be studied and analyzed if the noise present in the images is not modelled properly. There are different types of degradations which are considered such as noise, geometrical degradations, imperfections (due to improper illumination and color), and blur. Blurring in the images is generally caused by the relative motion between the camera and the original object being captured or due to poor focusing of an optical system. In the production of aerial photographs for remote sensing purposes, blurs are introduced by the atmospheric turbulence, aberrations in the optical system, and relative motion between the camera and the ground. Apart from the blurring effect, noise also creates imperfections in the images that corrupt the images under analysis. The noise may be introduced by several factors (e.g., medium, recording or capturing system, or by the quantization process). Due to this noise or blur present in the images, resolution needs to be improved and the image is to be restored from the geometrically warped, blurred, and noisy images.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.