Publication:
Performance Analysis of Adaptive Unsharp Masking Filter Techniques for Image Contrast Enhancement

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cris.author.scopus-author-id 57226532622
cris.author.scopus-author-id 22137274300
cris.author.scopus-author-id 57210438798
cris.author.scopus-author-id 36656186800
dc.contributor.author Ng S.M.
dc.contributor.author Yazid H.
dc.contributor.author Rahim S.A.
dc.contributor.author Mustafa N.
dc.date.accessioned 2024-10-02T14:22:25Z
dc.date.available 2024-10-02T14:22:25Z
dc.date.issued 2021-01-01
dc.description.abstract Image contrast enhancement is known as one of the important techniques applied in the field of image processing. In order to improve the contrast of the captured image, different adaptive Unsharp Masking Filter (UMF) techniques were proposed by the researchers. In this paper, the main contribution is the implementation of three algorithms namely adaptive gain adjustment approach using an UMF (ASAUMF), design of UMF kernel and gain using Particle Swarm Optimization (UMFKG) and lastly, intensity and edge-based adaptive UMF (IntEdgUMF) which is denoted as Algorithm 1, 2 and 3 respectively. These algorithms were tested on the standard and biometric images like face images. This is because these adaptive UMF were mainly applied to natural scenery, but the importance of high image quality is not limited to the environment but also to the other fields such as biometric identification. Based on the results, Algorithm 1 is able to achieve the highest average PSNR values of 31.6079 dB and 35.8052 dB when applied on Set14 and LFW databases respectively. Although Algorithm 1 needs a longer running time in producing the output images, this algorithm can emphasize the details or information from the input image by enhancing the contrast of the image. Thus, Algorithm 1 can be concluded as the best adaptive UMF techniques among the three algorithms tested. For future work, the use of these adaptive UMF can be implemented onto various images, for instance gray scale images or other biometric images in order to test the effectiveness of the algorithms in different applications.
dc.identifier.doi 10.1109/ICSET53708.2021.9612557
dc.identifier.isbn [9781665437660]
dc.identifier.scopus 2-s2.0-85123384965
dc.identifier.uri https://hdl.handle.net/20.500.14170/8311
dc.relation.funding Ministry of Higher Education, Malaysia
dc.relation.grantno undefined
dc.relation.ispartof 2021 IEEE 11th International Conference on System Engineering and Technology, ICSET 2021 - Proceedings
dc.relation.ispartofseries 2021 IEEE 11th International Conference on System Engineering and Technology, ICSET 2021 - Proceedings
dc.subject image contrast enhancement | Image processing | unsharp masking
dc.title Performance Analysis of Adaptive Unsharp Masking Filter Techniques for Image Contrast Enhancement
dc.type Conference Proceeding
dspace.entity.type Publication
oaire.citation.endPage 319
oaire.citation.startPage 315
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
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person.identifier.scopus-author-id 57226532622
person.identifier.scopus-author-id 22137274300
person.identifier.scopus-author-id 57210438798
person.identifier.scopus-author-id 36656186800
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