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Found 11 papers, 0 papers with code
Single Image Deraining via Feature-based Deep Convolutional Neural Network
A single image deraining algorithm based on the combination of data-driven and model-based approaches is proposed.
Single Image Deraining via Rain-Steaks Aware Deep Convolutional Neural Network
It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image.
Dual-Scale Single Image Dehazing Via Neural Augmentation
Model-based single image dehazing algorithms restore haze-free images with sharp edges and rich details for real-world hazy images at the expense of low PSNR and SSIM values for synthetic hazy images.
Adaptive Weighted Guided Image Filtering for Depth Enhancement in Shape-From-Focus
In order to preserve the edges accurately in the refined depth map, the guidance image is constructed from the multi-focus image sequence, and the coefficient of the AWGIF is utilized to suppress the noise while enhancing the fine depth details.
Ranked #8 on
Spectral Reconstruction
on ARAD-1K
Model-Based Single Image Deep Dehazing
Model-based single image dehazing algorithms restore images with sharp edges and rich details at the expense of low PSNR values.
Hybrid Saturation Restoration for LDR Images of HDR Scenes
It is an ill-posed problem to restore the saturated regions of the LDR image.
Single image dehazing via combining the prior knowledge and CNNs
If the transmission map of a pixel is small, the base layer of the haze image is used to recover a haze-free image via atmospheric scattering model, finally.
Multi-Scale Single Image Dehazing Using Laplacian and Gaussian Pyramids
Ambiguity between object radiance and haze and noise amplification in sky regions are two inherent problems of model driven single image dehazing.
Single Image Brightening via Multi-Scale Exposure Fusion with Hybrid Learning
In this paper, a single image brightening algorithm is introduced to brighten such an image.
Illumination Normalization via Merging Locally Enhanced Textures for Robust Face Recognition
Finally, the local contrast equalization (LCE) is performed on the fused face image to reduce the influence caused by over or under saturated pixel values in highlight or dark regions.
Exposure Interpolation by Combining Model-driven and Data-driven Methods
A natural question raised here is "Is there any space for conventional methods on these problems?"
