ORIGINAL PAPER
Research on mixed noise removal algorithm for ore images based on fusion filtering technique
1
Jiangxi University of Science and Technology，Faculty of Mechatronic Engineering
Submission date: 2024-06-05
Final revision date: 2024-07-27
Acceptance date: 2024-10-23
Publication date: 2024-12-17
Corresponding author
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2024;40(4):91-105
KEYWORDS
TOPICS
Scientific background of mineral resource managementRational and efficient development and utilization of mineral resourcesRational use of mineral raw materials
ABSTRACT
To meet the requirements of the image processing process on image quality, as the ore image contains Gaussian noise, pepper noise, Rayleigh noise, and other kinds of mixed noise is easy to destroy the real information of the image combined with the advantages of wavelet and non-local mean filtering, a new wavelet + non-local mean (NL-means) fusion denoising algorithm is proposed. Taking the ore image with mixed noise obtained from a mine as the research object, the wavelet function is used to carry out a two-dimensional wavelet transform on the filled image, separating the high and low-frequency information, setting the threshold vector to deal with the high-frequency wavelet coefficients, inverting the transform to get the first reconstructed image, followed by the second inverse transform. Then, the second reconstructed image is subjected to NL-mean denoising to remove the complex mixed noise in the ore image to the maximum extent. The experimental results show that the noise reduction performance of the fusion denoising algorithm has a greater improvement compared with the single filter and several other fusion algorithms. The peak signal-to-noise ratio of the denoised image is 31.0181dB. The structural similarity is 0.59913, which is 15.7584dB and 0.45241, respectively, compared with that before denoising. It has an obvious effect on the removal of the mixed noise in the ore image, which provides strong technical support to improve the noise removal of the ore image.
ACKNOWLEDGEMENTS
This study was supported by the National Natural Science Foundation of China (52364025).
CONFLICT OF INTEREST
The Authors have no conflicts of interest to declare.
METADATA IN OTHER LANGUAGES:
Polish
Badania nad algorytmem usuwania szumu mieszanego dla obrazów rudy w oparciu o technikę filtrowania fuzyjnego
algorytm odszumiania, szum mieszany, złożone warunki działania, przetwarzanie obrazu
Aby spełnić wymagania procesu przetwarzania obrazu dotyczące jakości obrazu, ponieważ obraz rudy zawiera szum Gaussa, szum pieprzowy, szum Rayleigha i inne rodzaje szumu mieszanego, łatwo jest zafałszować rzeczywiste dane obrazu w połączeniu z zaletami filtrowania falkowego i średniej nielokalnej, zaproponowano nowy algorytm odszumiania fuzji falkowej + średniej nielokalnej (NL-means). Biorąc obraz rudy z szumem mieszanym uzyskany z kopalni jako obiekt badawczy, funkcja falkowa jest używana do przeprowadzenia dwuwymiarowej transformacji falkowej na wypełnionym obrazie, oddzielając informacje o wysokiej i niskiej częstotliwości, ustawiając wektor progowy w celu radzenia sobie ze współczynnikami falkowymi o wysokiej częstotliwości, odwracając transformację w celu uzyskania pierwszego zrekonstruowanego obrazu, a następnie drugiej odwrotnej transformacji. Następnie drugi zrekonstruowany obraz jest poddawany odszumianiu NL-mean w celu usunięcia złożonego szumu mieszanego w obrazie rudy w maksymalnym stopniu. Wyniki eksperymentów pokazują, że wydajność redukcji szumu algorytmu odszumiania fuzji jest większa w porównaniu z pojedynczym filtrem i kilkoma innymi algorytmami fuzji. Szczytowy stosunek sygnału do szumu odszumionego obrazu wynosi 31,0181 dB. Podobieństwo strukturalne wynosi 0,59913, co stanowi odpowiednio 15,7584 dB i 0,45241 w porównaniu z tym przed odszumianiem. Ma to oczywisty wpływ na usuwanie szumu mieszanego w obrazie rudy, co zapewnia silne wsparcie techniczne w celu poprawy usuwania szumu obrazu rudy.
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| eISSN: | 2299-2324 |
| ISSN: | 0860-0953 |
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