Open AccessMedical Image Enhancement Using Recurrent Neural Networks Based Tv Homomorphic Filter
Author(s) -
Sweta Kumari,
Madhu Lata Nirmal
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40483
Subject(s) - homomorphic filtering , computer science , artificial intelligence , computer vision , digital image , brightness , image quality , image (mathematics) , homomorphic encryption , digital image processing , image processing , image enhancement , encryption , physics , optics , operating system
Image Enhancement is one of the important requirements in Digital Image Processing which is important in making an image useful for various applications which can be seen in the areas of Digital photography, Medicine, Geographic Information System, Industrial Inspection, Law Enforcement and many more Digital Image Applications. Image Enhancement is used to improve the quality of poor images. X-ray image contains a large amount of information and became important basis in the process of medical diagnosis. The X-ray image has large gray dynamic range but low contrast. This work proposed a new kind of homomorphic filter with ANN which uses total variation model as the transfer function. it has a good balance in both brightness adjustment and details enhancement. And the comparison results were given, the experimental results show that the method can effectively increase the image contrast, highlight the details. Index Terms: Medical image; X-ray image; total variation (TV); image enhancement; image de-noising; ANN