Open AccessMedical Image Enhancement through Dual Tree Complex Wavelet Transform and Multi-resolution Gabor Filter
Author(s) -
Gouri Morankar
Publication year - 2021
Publication title -
international journal of next-generation computing
Language(s) - English
Resource type - Journals
eISSN - 2229-4678
pISSN - 0976-5034
DOI - 10.47164/ijngc.v12i5.444
Subject(s) - artificial intelligence , complex wavelet transform , computer science , computer vision , gabor filter , pattern recognition (psychology) , filter (signal processing) , image processing , wavelet transform , wavelet , image (mathematics) , discrete wavelet transform
Medical image processing is essential in the field of clinical medicine for analysis and diagnosis of diseases. Most of these medical images are acquired under low illumination and noisy environment. Hence it produces a bottleneck in the processing of medical images through computer vision system. Due to tremendous details and complexity of the medical images, image enhancement is challenging and difficult task. In this paper, medical image enhancement through dual tree complex wavelet transform (DTCWT) and multi-resolution Gabor filter is proposed. After the medical images are acquired using standard techniques, DTCWT is applied that decomposes the gray scale image into high and low frequency subbands. Further DTCWT is applied twice on low frequency subbands to decompose into its high and low frequency subbands. Then multiresolution Gabor filter is applied to decomposed six high frequency subands and two low frequency subband to obtain enhancement in multiple directions. Finally inverse DTCWT is applied to obtain enhanced medical image. The experimental results demonstrate that the approach based on DTCWT and multi-resolution Gabor filter can produce better image enhancement as compared with the conventional and latest methods. The proposed medical image enhancement technique can be applied in analysis and diagnosis of diseases through computer vision system.