Grand Challenges in Radar Signal Processing

Gini, Fulvio

doi:10.3389/frsip.2021.664232

Cited by 17 publications

(10 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this method encountered issues of limited resolution and processing efficiency. Dufaux (2021) argued that technical challenges could remain in the supervised illumination enhancement. The supervised illumination enhancement approach requires a large and fully labelled training data set and involves a time-consuming as well as expensive process (Dufaux, 2021).…”

Section: Resultsmentioning

confidence: 99%

“…The supervised illumination enhancement approach requires a large and fully labelled training data set and involves a time-consuming as well as expensive process (Dufaux, 2021). The deep learning approach is often vulnerable to adversarial attacks (Dufaux, 2021; Akhtar and Mian, 2018). Therefore, it is difficult to achieve efficient outcomes having low complexity.…”

Section: Resultsmentioning

confidence: 99%

“…Issues such as mode collapse, non-convergence and stability are also common in the GANs training. Dufaux (2021) suggested that combining traditional processing techniques with deep learning models could generate a better outcome by enhancing low complexity solutions and preserving high image enhancement performance at the same time. To improve the accuracy and runtime performance of low-image enhancement, more research should be performed to extend the refined LIME approach and combine it with deep learning methods.…”

Section: Resultsmentioning

confidence: 99%

“…This method minimizes the dependency on paired training data and allows for larger varieties of images to be trained from 2021) argued that technical challenges could remain in the supervised illumination enhancement. The supervised illumination enhancement approach requires a large and fully labelled training data set and involves a time-consuming as well as expensive process (Dufaux, 2021). The deep learning approach is often vulnerable to adversarial attacks (Dufaux, 2021;Akhtar and Mian, 2018).…”

Section: Developmentmentioning

confidence: 99%

See 3 more Smart Citations

Development of a refined illumination and reflectance approach for optimal construction site interior image enhancement

Wong

Maghrebi²,

Fini³

et al. 2022

View full text Add to dashboard Cite

Purpose Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy. Design/methodology/approach To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress. Findings The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance. Originality/value The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Developmentmentioning

confidence: 99%

See 2 more Smart Citations

Development of a refined illumination and reflectance approach for optimal construction site interior image enhancement

Wong

Maghrebi²,

Fini³

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In recent decades, wireless communication systems have experienced rapid growth in the use of multiple-input multipleoutput (MIMO) technology in applications such as mobile radio networks, the Internet of things (IoT), and military and civilian radars [1,2]. Advantages such as higher data rate, reduced signal distortion and higher accuracy obtained through the use of multiple transmitter (Tx) and receiver (Rx) combinations, have been among the reasons for the increasing development of this technology compared to conventional technologies such as single-input single-output (SISO) and single-input multiple-output (SIMO) [3].…”

Section: Introductionmentioning

confidence: 99%

A multi-resolution analysis-based approach to accelerate data acquisition for near-field MIMO millimeter-wave imaging

Molaei

Hu²,

Fusco³

et al. 2022

Passive and Active Millimeter-Wave Imaging XXV

View full text Add to dashboard Cite

An approach to designing multiple waveforms in a multiple-input multiple-output (MIMO) system is presented so that the full capacity of the transmitting and receiving antennas can be utilized at the same time. On the transmitter-side, the antenna elements are classified into different groups according to their specific signal. On the receive-side, we use a multi-resolution analysis to retrieve the signals of each channel. Due to the superior characteristics of the FMCW signal, especially in terms of sampling, in the proposed approach, an FMCW radar is considered. To adapt the introduced system to multistatic near-field imaging, we use more accurate models than the effective phase center principle. This contributes to the successful reconstruction of the scene image by efficient Fourier-based image reconstruction methods. The performance of the proposed approach is confirmed by numerical simulations.

show abstract