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Article

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

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Istituto per le Applicazioni del Calcolo ‘Mario Picone’, Consiglio Nazionale delle Ricerche, Via dei Taurini 19, 00185 Roma, Italy
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Istituto per le Metodologie di Analisi Ambientale, Consiglio Nazionale delle Ricerche, C.da Santa Loja, Tito Scalo, 85050 Potenza, Italy
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Istituto per la Microelettronica e Microsistemi, Consiglio Nazionale delle Ricerche, Via Pietro Castellino 111, 80131 Napoli, Italy
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Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(3), 414; https://doi.org/10.3390/rs12030414
Received: 16 January 2020 / Revised: 20 January 2020 / Accepted: 22 January 2020 / Published: 28 January 2020
(This article belongs to the Special Issue GPU Computing for Geoscience and Remote Sensing)
We introduce a multi-platform portable implementation of the NonLocal Means methodology aimed at noise removal from remotely sensed images. It is particularly suited for hyperspectral sensors for which real-time applications are not possible with only CPU based algorithms. In the last decades computational devices have usually been a compound of cross-vendor sets of specifications (heterogeneous system architecture) that bring together integrated central processing (CPUs) and graphics processor (GPUs) units. However, the lack of standardization resulted in most implementations being too specific to a given architecture, eliminating (or making extremely difficult) code re-usability across different platforms. In order to address this issue, we implement a multi option NonLocal Means algorithm developed using the Open Computing Language (OpenCL) applied to Hyperion hyperspectral images. Experimental results demonstrate the dramatic speed-up reached by the algorithm on GPU with respect to conventional serial algorithms on CPU and portability across different platforms. This makes accurate real time denoising of hyperspectral images feasible. View Full-Text
Keywords: remote sensing; image processing; multispectral; hyperspectral; denoising; NonLocal Means; GPU; OpenCL; PRISMA, portability; Hyperion remote sensing; image processing; multispectral; hyperspectral; denoising; NonLocal Means; GPU; OpenCL; PRISMA, portability; Hyperion
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MDPI and ACS Style

Granata, D.; Palombo, A.; Santini, F.; Amato, U. Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm. Remote Sens. 2020, 12, 414. https://doi.org/10.3390/rs12030414

AMA Style

Granata D, Palombo A, Santini F, Amato U. Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm. Remote Sensing. 2020; 12(3):414. https://doi.org/10.3390/rs12030414

Chicago/Turabian Style

Granata, Donatella, Angelo Palombo, Federico Santini, and Umberto Amato. 2020. "Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm" Remote Sensing 12, no. 3: 414. https://doi.org/10.3390/rs12030414

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