Implementation of the image super-resolution DWT based algorithm on Raspberry Pi platform for real-time applications

Raul J. Osorno-Ortiz; Volodymyr I. Ponomaryov; Rogelio Reyes-Reyes; Clara Cruz-Ramos; Beatriz P. Garcia-Salgado; Sergiy Sadovnychiy

doi:10.1117/12.3017319

20 June 2024 Implementation of the image super-resolution DWT based algorithm on Raspberry Pi platform for real-time applications

Raul J. Osorno-Ortiz, Volodymyr I. Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz P. Garcia-Salgado, Sergiy Sadovnychiy

Author Affiliations +

Proceedings Volume 13000, Real-time Processing of Image, Depth, and Video Information 2024; 1300008 (2024) https://doi.org/10.1117/12.3017319
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

Super resolution (SR) is a technique designed for increasing the spatial resolution in an image from a low resolution (LR) to high resolution (HR) size. SR technology has had a considerable demand in a wide variety of applications to recover HR images, such as medicine, engineering, computer vision, pattern recognition and video production, etc. In contrast to interpolation-based algorithms that often introduce distortions or irregular borders, this study proposes an implementation that can preserve the edges and fine details of an original image through the computation of the wavelet decomposition. Different Discrete Wavelet Transform (DWT) families such as: Daubechies, Symlet, and Coiflet were evaluated. The proposed system was implemented on a Raspberry Pi 4 model B, an embedded device, to get around the PC’s mobility limitations, making it possible to create an in-expensive and energy-efficient SR system, reducing their complexity in realtime applications. To investigate the visual performance, SR images have been analysed in subjective matter via human perception view, guaranteeing good perception for the images of different nature from three different datasets such as Full– HD (DIV2K), medical (Raabin WBC), and remote sensing (Sentinel-1). The experimental results of designed implementations appear to demonstrate good performance in commonly used objective criteria: execution time, SSIM, and PSNR (0.742 sec., 0.9164, and 38.72 dB), respectively for images with a super resolution size of 1356 x 2040 pixels.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Raul J. Osorno-Ortiz, Volodymyr I. Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz P. Garcia-Salgado, and Sergiy Sadovnychiy "Implementation of the image super-resolution DWT based algorithm on Raspberry Pi platform for real-time applications", Proc. SPIE 13000, Real-time Processing of Image, Depth, and Video Information 2024, 1300008 (20 June 2024); https://doi.org/10.1117/12.3017319

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