Highly parallel image co-registration techniques using GPUs

Passerone, Claudio; Sansoè, Claudio; Maggiora, Riccardo; Avolio, Corrado; Zavagli, Massimo; Minati, Federico; Costantini, E.

doi:10.1109/aero.2014.6836384

Cited by 5 publications

(2 citation statements)

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“…The most successful application can be considered the spectral unmixing, where, among other things, algorithms have been developed for estimating the Pixel Purity Index [16], endmember identification [17,18], matrix factorization [19] and unmixing [20,21]. Among other remote sensing applications we recall orthorectification [22], image registration [23], NDVI computation [24] and classification [25,26].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…Image geometrical registration is widely used in many fields such as image processing [1, 2], computer vision [3, 4] and pattern recognition [5, 6]. The methods of image geometrical registration can be divided into rigid and non‐rigid registrations, and the rigid registration is mainly divided into two kinds: pixel‐ and feature‐based methods [7, 8].…”

Section: Introductionmentioning

confidence: 99%