About some compression algorithms [PDF]
arXiv, 2023 We use neural network algorithms for finding compression methods of images in the framework of iterated function systems which is a collection of the transformations of the interval $(0, 1)$ satisfying suitable properties.
arxiv
State-of-the-art in 360° Video/Image Processing: Perception, Assessment and Compression [PDF]
arXiv, 2019 Nowadays, 360{\deg} video/image has been increasingly popular and drawn great attention. The spherical viewing range of 360{\deg} video/image accounts for huge data, which pose the challenges to 360{\deg} video/image processing in solving the bottleneck of storage, transmission, etc.
arxiv
Temporal error concealment for fisheye video sequences based on equisolid re-projection [PDF]
European Signal Processing Conference (EUSIPCO), 2015, pp.
1611-1615, 2022 Wide-angle video sequences obtained by fisheye cameras exhibit characteristics that may not very well comply with standard image and video processing techniques such as error concealment. This paper introduces a temporal error concealment technique designed for the inherent characteristics of equisolid fisheye video sequences by applying a re ...
arxiv
IRXCT: Iterative Reconstruction and visualization application for X-ray Computed Tomography [PDF]
arXiv, 2019 This report describes the IRXCT Windows application for reconstruction and visualization of tomography tasks.
arxiv
Exploiting Temporal Attention Features for Effective Denoising in Videos [PDF]
arXiv, 2020 Video Denoising is one of the fundamental tasks of any videoprocessing pipeline. It is different from image denoising due to the tem-poral aspects of video frames, and any image denoising approach appliedto videos will result in flickering. The proposed method makes use oftemporal as well as spatial dimensions of video frames as part of a two-stage ...
arxiv
Video Reconstruction from a Single Motion Blurred Image using Learned Dynamic Phase Coding [PDF]
arXiv, 2021 Video reconstruction from a single motion-blurred image is a challenging problem, which can enhance the capabilities of existing cameras. Recently, several works addressed this task using conventional imaging and deep learning. Yet, such purely-digital methods are inherently limited, due to direction ambiguity and noise sensitivity. Some works proposed
arxiv
A Multi-scale Video Denoising Algorithm for Raw Image [PDF]
arXiv, 2022 Video denoising for raw image has always been the difficulty of camera image processing. On the one hand, image denoising performance largely determines the image quality, moreover denoising effect in raw image will affect the accuracy of the following operations of ISP processing flow.
arxiv
ViSTRA3: Video Coding with Deep Parameter Adaptation and Post Processing [PDF]
arXiv, 2021 This paper presents a deep learning-based video compression framework (ViSTRA3). The proposed framework intelligently adapts video format parameters of the input video before encoding, subsequently employing a CNN at the decoder to restore their original format and enhance reconstruction quality.
arxiv
Automatic Intracranial Brain Segmentation from Computed Tomography Head Images [PDF]
arXiv, 2019 Fast and automatic algorithm to segment Brain (intracranial region) from computed tomography (CT) head images using combination of HU thresholding, identification of intracranial voxels through ray intersection with cranium, special binary erosion and connected components per slice.
arxiv
Classification of optics-free images with deep neural networks [PDF]
arXiv, 2020 The thinnest possible camera is achieved by removing all optics, leaving only the image sensor. We train deep neural networks to perform multi-class detection and binary classification (with accuracy of 92%) on optics-free images without the need for anthropocentric image reconstructions.
arxiv