Morphological processor for real-time image applications

González, Francisco Javier Miranda; Dieste, Óscar; Tobajas, F.; Armas, V. de; Esper-Chain, R.; Sarmiento, Roberto

doi:10.1016/s0026-2692(02)00117-9

Cited by 11 publications

(5 citation statements)

References 3 publications

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“…Also, the proposed algorithm is based on morphological operators. Strategies of accelerating the calculation of the morphological operators, such as hardware acceleration [19,55], structuring element decomposition [56], and so on, can also be used by the proposed algorithm to decrease the calculation time. Therefore, the proposed image fusion algorithm may be widely used in different applications.…”

Section: Quantitative Comparison Resultsmentioning

confidence: 99%

Image analysis through feature extraction by using top-hat transform-based morphological contrast operator

Bai

2013

Appl. Opt.

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Image decomposition and reconstruction is an important way for image analysis. To be effective for image decomposition and reconstruction, a method using extracted features through top-hat transform-based morphological contrast operator (MCOTH) is proposed in this paper. First, the morphological contrast operator constructed using the top-hat transforms is discussed. Then, extracting the bright and dark image features in the result of MCOTH is given. Based on the extracted bright and dark image features, the original images are decomposed into multiscale complete decompositions using multiscale structuring elements. After processing the decomposed images following different application purposes, the final result image can be reconstructed from the processed decomposition images. To verify the effectiveness of the proposed image analysis method through image decomposition and reconstruction, the application of image enhancement and fusion are discussed. The experimental results show that because the proposed image decomposition and reconstruction method reasonably decomposes the original image into complete decomposition with useful image features at different scales, the useful image features could be easily used for different applications. After the useful image features are processed, the final result image could be reconstructed. Moreover, different types of images are used in the experiments of image enhancement and fusion, and the results are effective. Therefore, the proposed image decomposition and reconstruction method in this paper are effective methods for image analysis and could be widely used in different applications.

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Section: Quantitative Comparison Resultsmentioning

confidence: 99%

Image analysis through feature extraction by using top-hat transform-based morphological contrast operator

Bai

2013

Appl. Opt.

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“…This may increase the calculation time of the proposed algorithm. However, morphological operators have accelerating strategies (Droogenbroeck and Talbot, 1996;Gonzalez et al, 2002;Park and Chin, 1995) to speed up the calculation of the operators, such as structuring element decomposition, parallel calculation and so on. By using these strategies, the proposed algorithm may be performed fast.…”

Section: Quantitative Comparisonmentioning

confidence: 99%

Mineral image enhancement based on sequential combination of toggle and top-hat based contrast operator

Bai

2013

Micron

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“…However, accelerating of the calculation of morphological operations, such as appropriate utilization of the parallel property of morphological operations [15], hardware acceleration [26], and structuring element decomposition [27], could apparently de- crease the calculation time of morphological operations, which could be also used in the proposed algorithm to decrease the calculation time. Some strategies to accelerate the calculation of morphological operations could be found in some related literatures [15,[26][27][28].…”

Section: Calculation Time Comparisonmentioning

confidence: 99%

“…Some strategies to accelerate the calculation of morphological operations could be found in some related literatures [15,[26][27][28]. Also, effective implementation of the proposed algorithm and using small number of scales will also apparently decrease the calculation time.…”

Section: Calculation Time Comparisonmentioning

confidence: 99%

Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform

Bai

Zhou

Xue

2011

Infrared Physics & Technology

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Morphological processor for real-time image applications

Cited by 11 publications

References 3 publications

Image analysis through feature extraction by using top-hat transform-based morphological contrast operator

Image analysis through feature extraction by using top-hat transform-based morphological contrast operator

Mineral image enhancement based on sequential combination of toggle and top-hat based contrast operator

Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform

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