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MULTIFOCUS IMAGE FUSION USING WAVELET TRANSFORM, GRADIENT AND MATHEMATICA

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dc.contributor.author IQBAL, MUHAMMAD
dc.date.accessioned 2023-08-29T06:58:39Z
dc.date.available 2023-08-29T06:58:39Z
dc.date.issued 2008
dc.identifier.other [2006-NUST-MS PhD-CSE (E)-01]
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/37800
dc.description Supervisor: DR MUHAMMAD YOUNUS JAVED en_US
dc.description.abstract Image fusion has its applications in many fields such as computer vision, automatic object detection, robotics, remote sensing, military and law enforcement, medical imaging and manufacturing. The objective of image fusion is to generate a resultant fused image from a set of input images (of the same scene) which describes the scene better than any single input image with respect to some relevant properties. The fused image is obtained by extracting all the useful information from the source images while not introducing artifacts or inconsistencies which will distract human observers or the following processing. For this purpose a new image fusion technique that is actually integration of multi-scale wavelet transform, gradient and mathematical morphology schemes, has been proposed. The proposed scheme’s implementation mainly consists of five steps. The first step is the application of discrete wavelet transform on the set of multifocused source images. The second step deals with the computation of local gradient of each detailed wavelet coefficient block. Finding of image activity level is the next step. Generation of binary decision map takes place based on image activity levels obtained at the previous step. Different morphological operations have been performed on binary decision map that separate the focus and defocused parts of the input images. Finally, fused image has been achieved by using the processed binary decision map. The empirical results on standard test images (i.e. Lena, Barbara, Gold Hill and Peppers) provide higher Peak Signal to Noise Ratio (PSNR) and smaller Root Mean Square Error (RMSE) values than some of the previous approaches. These fusion results strengthen the idea of using combination of multi-scale wavelet transform, gradient and mathematical morphology schemes for multifocus image fusion. MATLAB 7.0 has been used for the implementation of the proposed approach. Experiments have been carried out on a variety of standard greyscale images with different defocus parts. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.title MULTIFOCUS IMAGE FUSION USING WAVELET TRANSFORM, GRADIENT AND MATHEMATICA en_US
dc.type Thesis en_US


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