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Found 12 papers, 10 papers with code
An Unsupervised Generative Neural Approach for InSAR Phase Filtering and Coherence Estimation
GenInSAR's Phase, and Coherence Root-Mean-Squared-Error and Phase Cosine Error have average improvements of 0. 54, 0. 07, and 0. 05 respectively compared to the related methods.
Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework
Complete disparity maps are reconstructed from boundaries' disparities.
CNN-Based Real-Time Parameter Tuning for Optimizing Denoising Filter Performance
We propose a novel direction to improve the denoising quality of filtering-based denoising algorithms in real time by predicting the best filter parameter value using a Convolutional Neural Network (CNN).
CNN-based InSAR Coherence Classification
Interferometric Synthetic Aperture Radar (InSAR) imagery based on microwaves reflected off ground targets is becoming increasingly important in remote sensing for ground movement estimation.
A hybrid algorithm for disparity calculation from sparse disparity estimates based on stereo vision
In this paper, we have proposed a novel method for stereo disparity estimation by combining the existing methods of block based and region based stereo matching.
Adaptive Dithering Using Curved Markov-Gaussian Noise in the Quantized Domain for Mapping SDR to HDR Image
We vary the magnitude and structure of the noise pattern adaptively based on the luma of the quantized pixel and the slope of the inverse-tone mapping function.
CNN-based InSAR Denoising and Coherence Metric
Interferometric Synthetic Aperture Radar (InSAR) imagery for estimating ground movement, based on microwaves reflected off ground targets is gaining increasing importance in remote sensing.
Potential of deep features for opinion-unaware, distortion-unaware, no-reference image quality assessment
However, majority of such methods either use hand-crafted features or require training on human opinion scores (supervised learning), which are difficult to obtain and standardise.
DeepInSAR: A Deep Learning Framework for SAR Interferometric Phase Restoration and Coherence Estimation
In this work, we propose a deep convolutional neural network (CNN) based model DeepInSAR to intelligently solve both the phase filtering and coherence estimation problems.
A Fast Segmentation-free Fully Automated Approach to White Matter Injury Detection in Preterm Infants
We detect the ventricles as blobs using a fast linear Maximally Stable Extremal Regions algorithm.
Highlighting objects of interest in an image by integrating saliency and depth
However, the depth information acquired from stereo can also be used along with saliency to highlight certain objects in a scene.
Entropy-difference based stereo error detection
As a remedy, we propose a novel error detection approach based solely on the input image and its depth map.
