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Comparison of two image denoising approaches based on compressive sensing principles
Starting from the realistic assumption that digital images are highly concentrated in the
domain of the two-dimensional discrete cosine transform (2D-DCT), we have exploited …
domain of the two-dimensional discrete cosine transform (2D-DCT), we have exploited …
Salient Preprocessing: Robotic ICP Pose Estimation Based on SIFT Features
L Hu, Y Zhang, Y Wang, G Ge, W Wang - Machines, 2023 - mdpi.com
The pose estimation can be effectively solved according to the feature point matching
relationship in RGB-D. However, the extraction and matching process based on the whole …
relationship in RGB-D. However, the extraction and matching process based on the whole …
SAR Despeckling via Log-Yeo-Johnson Transformation and Sparse Representation
Synthetic Aperture Radar (SAR) images are widely used in remote sensing due to their all-
weather, all-day imaging capabilities. However, SAR images are highly susceptible to noise …
weather, all-day imaging capabilities. However, SAR images are highly susceptible to noise …
Image denoising algorithm for IoT based on compressive sensing principle and Blackfin microcontrollers
This paper analyzes and evaluates the performance of an algorithm for image denoising
using compressive sensing principle and discrete cosine transform. The random sample …
using compressive sensing principle and discrete cosine transform. The random sample …
Roadway Disease Identification Based on RANSAC and A-Shape in the Context of BIM Technology
Y Wang - 2024 International Symposium on Intelligent Robotics …, 2024 - ieeexplore.ieee.org
Most road surfaces in China inevitably experience deformation, cracks, or the formation of
potholes due to long-term erosion by natural climate and pressure caused by vehicle …
potholes due to long-term erosion by natural climate and pressure caused by vehicle …
[CITATION][C] ISTA-DNet-Image de-noising using deep unfolded compressive sensing. The use case of brain and knee MRI
P Kurtser, A Garpebring - Medical Imaging with Deep Learning, 2024