Search
Search Results
-
A deep learning based multi-image compression technique
A multi-image compression technique compresses multiple images of the same or various sizes together to generate a common codebook. In multi-image...
-
A Single Image High-Perception Super-Resolution Reconstruction Method Based on Multi-layer Feature Fusion Model with Adaptive Compression and Parameter Tuning
We propose a simple image high-perception super-resolution reconstruction method based on multi-layer feature fusion model with adaptive compression...
-
Iterative shrinkage thresholding-based anti-multi-noise compression perceptual image reconstruction network
Telemedicine imaging services usually require wireless transmission of a large number of medical images MRI/CT, etc., in the network, which are...
-
Development of Multi-Image Compression Technique Based on Common Code Vector
In the field of data compression, the performance of an image compression technique based on the amount of compression ratio achieved keeps the...
-
Multi-scale gradient wavelet-based image quality assessment
The quality of images is always at stake due to the abundant compression, transferring, and processes done on them. Each of which brings about its...
-
SFPN: segmentation-based feature pyramid network for multi-focus image fusion
In multi-focus image fusion, different targets often have different sizes, and the network with poor multi-scale feature extraction ability will...
-
Compressed sensing based visually secure multi-secret image encryption-sharing scheme
The existing encryption schemes of visually secure image have drawbacks, such as excessive concentration of image data and insufficient resistance to...
-
Multi-granularity sequence generation for hierarchical image classification
Hierarchical multi-granularity image classification is a challenging task that aims to tag each given image with multiple granularity labels...
-
Multi-scale siamese networks for multi-focus image fusion
In this paper, we propose a multi-scale Siamese network for multi-focus image fusion. Many current image fusion methods are based on classifier and...
-
Image splicing manipulation location by multi-scale dual-channel supervision
The swift growth of diverse editing software has resulted in image splicing manipulation becoming more complex, the discovery of a meticulously...
-
Image inpainting via multi-resolution network with Fourier convolutions
Image inpainting has been a trending topic among researchers in recent years, which aims to fill missing areas in images while maintaining visual and...
-
A survey of multi-source image fusion
Multi-source image fusion has become an important and useful new technology in the image understanding and computer vision fields. The purpose of...
-
METER: Multi-task efficient transformer for no-reference image quality assessment
AbstractNo-reference image quality assessment (NR-IQA) is a fundamental yet challenging task in computer vision. Current NR-IQA methods based on...
-
Adaptive multi-information distillation network for image dehazing
Image dehazing is a challenging low-level vision task that estimates potentially haze-free images from hazy images. In recent years, convolutional...
-
PTIFNet: Pseudo-Twin network for multi-focus image fusion
In this paper, we propose a multi-focus image fusion network based on the classical pseudo-twin two-branch network, called PTIFNet, which can...
-
Full reference image quality assessment based on dual-space multi-feature fusion
At present, the majority of techniques for assessing image quality are limited to extracting features from an image in a single space. This paper...
-
Ghost-Unet: multi-stage network for image deblurring via lightweight subnet learning
Multi-stage networks function by applying the concept of cascading, which alleviates the difficulties of network structure optimization using the...
-
MadFormer: multi-attention-driven image super-resolution method based on Transformer
While the Transformer-based method has demonstrated exceptional performance in low-level visual processing tasks, it has a strong modeling ability...
-
Dual parallel multi-scale residual overlay network for single-image rain removal
Rain not only degrades the perceptual image quality, but also destroys the visibility of the scene, which affects the computer vision algorithms’...
-
Lightweight transformer and multi-head prediction network for no-reference image quality assessment
No-reference (NR) image quality assessment (IQA) is an important task of computer vision. Most NR-IQA methods via deep neural networks do not reach...
