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The paper deals with the issue of multifocal image fusion. Two techniques of the hierarchical image representation are analyzed
herein. The first one is hierarchical decomposition based on the Laplacian pyramid and the second one is based on integer discrete
wavelet transformation. After the analysis of the above-mentioned decompositions techniques...
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... edges than the blurred image. Hence, the energy of the differentiated version of the focused image must be higher than the energy of the blurred one. By simple comparison of the blocks energy of the differentiated images, the approximation image used for the image fusion can be obtained. The input microscopic multifocal images of PCB are shown in Fig. 4a), b). The images show Integrated Circuit (IC) with high package and SMD components. The image where the microscope is focused on the surface of SMDs and PCB is shown in Fig. 4a), while in Fig. 4b), on the contrary, the microscope is focused on the surface of IC. Fig. 4c), d) shows the results of edge detection for the first level of GP. ...
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... blocks energy of the differentiated images, the approximation image used for the image fusion can be obtained. The input microscopic multifocal images of PCB are shown in Fig. 4a), b). The images show Integrated Circuit (IC) with high package and SMD components. The image where the microscope is focused on the surface of SMDs and PCB is shown in Fig. 4a), while in Fig. 4b), on the contrary, the microscope is focused on the surface of IC. Fig. 4c), d) shows the results of edge detection for the first level of GP. Fig. 5 represents a block diagram of the complete algorithm of the multifocal image fusion. Fig. 5 shows that input images (A and B) are decomposed into subimage of IDWT or LP. ...
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... differentiated images, the approximation image used for the image fusion can be obtained. The input microscopic multifocal images of PCB are shown in Fig. 4a), b). The images show Integrated Circuit (IC) with high package and SMD components. The image where the microscope is focused on the surface of SMDs and PCB is shown in Fig. 4a), while in Fig. 4b), on the contrary, the microscope is focused on the surface of IC. Fig. 4c), d) shows the results of edge detection for the first level of GP. Fig. 5 represents a block diagram of the complete algorithm of the multifocal image fusion. Fig. 5 shows that input images (A and B) are decomposed into subimage of IDWT or LP. Subimages of ...
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... can be obtained. The input microscopic multifocal images of PCB are shown in Fig. 4a), b). The images show Integrated Circuit (IC) with high package and SMD components. The image where the microscope is focused on the surface of SMDs and PCB is shown in Fig. 4a), while in Fig. 4b), on the contrary, the microscope is focused on the surface of IC. Fig. 4c), d) shows the results of edge detection for the first level of GP. Fig. 5 represents a block diagram of the complete algorithm of the multifocal image fusion. Fig. 5 shows that input images (A and B) are decomposed into subimage of IDWT or LP. Subimages of details are directly fused by application of (6). Thus, the combined subimages are ...
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Citations
... The discrete wavelet transform (DWT) and discrete multiwavelet transform (DMWT) became very popular in the last few decades. The transforms are used in a wide spectrum of applications, for example, we can mention compression [1][2][3], classification [4], multifocal and multi-exposure images fusion [5,6], medical image denoising [7], human emotion detection [8], image steganography [9,10] and many others. One of drawbacks of the classical DWT is that during the signal or image analysis it uses only one scale and one wavelet function. ...
... The concerned multiwavelets are DGHM [4], CL created by Chui and Lian [5], symmetric-antisymmetric SA4 [6,7] and BiHermite [8] therefore the article deals only with DMWT using these multiwavelets. Below equations (2),(3) define the impulse responses of two multifilters for DGHM. ...
... Below equations (2),(3) define the impulse responses of two multifilters for DGHM. For implementation of DMWT with multiwavelet CL the matrix impulse responses of multifilters are defined by (4), (5) and the impulse responses for SA4 multiwavelet by (6), (7), while the multiwavelet BiHermite is defined by (8), (9). ...
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... This is done by summation of a Laplacian and input images. The Laplacian image is created by subtraction the Gaussian image from the input image [14,15,16]. This step is not necessary for detection, but it improves the results. ...
... For the purposes of classification we use DWT with db3 wavelet. As it is known, DWT is done by division of an input signal into two branches where it is filtered by LP and HP filters [8,9,10,11]. These filtered versions of the signal are decimated by factor 2. By this process decomposition of the signal into details and approximation subimages is achieved. ...
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Vysokoškolská učebnica vznikla na Katedre technológií v elektronike FEI TU v Košiciach na základe dlhodobej vedeckej a pedagogickej činnosti autora v danej oblasti. Je určená pre študentov bakalárskeho, inžinierskeho a doktorandského štúdia hlavne v odboroch elektroniky, automobilovej a inteligentnej elektroniky, telekomunikácii ale aj iných odborov, v ktorých sa vyskytuje problematika spracovania obrazov. Učebnica, ako už z jej názvu vyplýva, pojednáva o najzákladnejších problémoch, ktoré by si študent v úvode do oblasti spracovania obrazov mal osvojiť.
