Solving nonlinear equation systems (NESs) is a challenging problems in numerical computation. Two goals should be considered for solving NESs. One is to locate as many roots as possible and the other is to improve the...
详细信息
In this contribution, an objective metric for quality evaluation of light field images is presented. the method is based on the exploitation of the depth information of a scene, that is captured with high accuracy by ...
A method for image stitching is presented. the approach focuses on images with parallax (depth variation) to create panoramic views with high fidelity. the approach creates the stitching seam at a virtual depth to con...
详细信息
Depth estimation approaches are crucial for environment perception in applications like autonomous driving or driving assistance systems. Solutions using cameras have always been preferred to other depth estimation me...
详细信息
ISBN:
(纸本)9781665409773
Depth estimation approaches are crucial for environment perception in applications like autonomous driving or driving assistance systems. Solutions using cameras have always been preferred to other depth estimation methods, due to low sensor prices and their ability to extract rich semantic information from the scene. Monocular depth estimation algorithms using CNNs may fail to reconstruct due to unknown geometric properties of certain objects or scenes, which may not be present during the training stage. Furthermore, stereo reconstruction methods, may also fail to reconstruct some regions for various other reasons, like repetitive surfaces, untextured areas or solar flares to name a few. To mitigate the reconstruction issues that may appear, in this paper we propose two refinement approaches that eliminate regions which are not correctly reconstructed. Moreover, we propose an original architecture for combining the mono and stereo results in order to obtain improved disparity maps. the proposed solution is designed to be fault tolerant such that if an image is not correctly acquired or is corrupted, the system is still able to reconstruct the environment. the proposed approach has been tested on the KITTI dataset in order to illustrate its performance.
the work is devoted to implementing traditional technologies of visual monitoring of plants for precision agriculture technologies, namely data engineering for the improvement of remote monitoring of marker vegetation...
详细信息
ISBN:
(纸本)9798350334326
the work is devoted to implementing traditional technologies of visual monitoring of plants for precision agriculture technologies, namely data engineering for the improvement of remote monitoring of marker vegetation indices withthe help of UAVs. Classic vegetation indices such as NDVI that used to solve a limited range of problems and them mainly used to adjust the number of nitrogen fertilizers during differentiated treatment of field areas. Such indices are poorly adapted to identify the causes of stress. For stresses of a technical nature, in particular, on winter rapeseed crops, marker indices are used, which, withthe traditional model of color formation, are difficult to adjust to identify anomalous coloration of affected plants. In addition, the accuracy of classical indices for the additive color formation model is affected by changes in lighting, increasing the accuracy of anomaly identification requires additional adjustment based on the state of the atmosphere at the time of image acquisition. the purpose of the work is the formation of a new approach to the automation of visual diagnostics of plants, which is based on the adaptation of machine vision technologies to the existing technologies of noncontact expert assessment of plants. A hypothesis was put forward about the possibility of creating vegetation indices based on an alternative model of HSL coloration, which would be more resistant to changes in illumination. the research was carried out on winter wheat crops in April-May 2021, archival images of winter rapeseed crops affected by technological stress taken in 2019 were also used. Photography was carried out using a Phantom 2 UAV in the visible range of the spectrum. Data processing was performed in the MathCad environment. the research was conducted on the resistance to changes in lighting during hardware adjustment of the exposure of images, as well as the features of object identification, namely, healthy and affected leaves and soil in th
In this study, we propose an image despeckling method based on low-rank Hankel matrix approach and speckle level estimation. Annihilating filter-based low-rank Hankel matrix, so called ALOHA approach is very useful to...
详细信息
In this paper, a single image multi-scale super-resolution technique is proposed. the concept under study is the learning procedure between steps of amplification in order to predict the next high scale of resolution....
详细信息
Multi-resolution imageprocessing are part of this concept that has a purpose to extracting the detail information of the multi-scale input image. However, in general, to process a multi-scale imagethere are issue th...
详细信息
Shannon information capacity, which can be expressed as bits per pixel or megabits per image, is an excellent figure of merit for predicting camera performance for a variety of machine vision applications, including m...
详细信息
Recently, 3D time-of-flight cameras have been developed. the development enables utilization of depthimages in various fields. However, acquired depthimages are corrupted by noise during the image acquisition proces...
详细信息
暂无评论