Closing in on Cracks

1998 ◽  
Vol 120 (07) ◽  
pp. 68-69
Author(s):  
Henry Baumgartner
Keyword(s):  
High Resolution ◽  
Digital Camera ◽  
Field Size ◽  
Reference Library ◽  
Advanced Imaging ◽  
Technology Center ◽  
Basic Issue ◽  
Reference Images ◽  
Flexible Imaging ◽  
Associated Data

This article focuses on a high-resolution digital camera that provides fast, flexible imaging for photomicrography and microscopy. Digital images are not only equal in quality to traditional images, but they are also three times faster to acquire, less expensive, easier to distribute, and more useful as reference images for future analysis. In terms of quality, the basic issue is matching images on 4-by-5-inch instant film, and recording the same field size with the same resolution. Reports with embedded digital image links are issued over the LAN so users do not have to seek out images separately on the Technology Center server. The department is also creating a reference library of microstructure images that have been captured digitally. Image Central software from Advanced Imaging Concepts in Princeton, N.J., is to be used to create the database with reference images and associated data.

scholarly journals Pine wilt disease detection in high-resolution UAV images using object-oriented classification

2021 ◽  
Author(s):  
Zhao Sun ◽  
Yifu Wang ◽  
Lei Pan ◽  
Yunhong Xie ◽  
Bo Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Digital Camera ◽  
Object Oriented ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Segmentation Algorithm ◽  
Tree Crown ◽  
Multi Scale ◽  
Pine Wilt

AbstractPine wilt disease (PWD) is currently one of the main causes of large-scale forest destruction. To control the spread of PWD, it is essential to detect affected pine trees quickly. This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD. We used an unmanned aerial vehicle (UAV) platform equipped with an RGB digital camera to obtain high spatial resolution images, and multi-scale segmentation was applied to delineate the tree crown, coupling the use of object-oriented classification to classify trees discolored by PWD. Then, the optimal segmentation scale was implemented using the estimation of scale parameter (ESP2) plug-in. The feature space of the segmentation results was optimized, and appropriate features were selected for classification. The results showed that the optimal scale, shape, and compactness values of the tree crown segmentation algorithm were 56, 0.5, and 0.8, respectively. The producer’s accuracy (PA), user’s accuracy (UA), and F1 score were 0.722, 0.605, and 0.658, respectively. There were no significant classification errors in the final classification results, and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation. The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing. This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.

An Ultra-High Resolution Digital Camera

1994 ◽  
Vol 42 (2) ◽  
pp. 49-51 ◽  
Author(s):  
L.W. MacDonald ◽  
R. Lenz
Keyword(s):  
High Resolution ◽  
Digital Camera

Integration of DV Based Motion Information and High-Resolution Digital Camera Image Information

2004 ◽  
Vol 2004.7 (0) ◽  
pp. 347-348
Author(s):  
Yoshihiko NOMURA ◽  
Ryutaro MATSUDA ◽  
Tokuhiro SUGIURA ◽  
Hirokazu Matsui ◽  
Norihiko KATO
Keyword(s):  
High Resolution ◽  
Digital Camera ◽  
Motion Information ◽  
Image Information ◽  
Camera Image

High-Resolution Paleoclimatic Information from Chinese Eolian Sediments Based on Grayscale Intensity Profiles

2000 ◽  
Vol 53 (1) ◽  
pp. 70-77 ◽  
Author(s):  
Stephen C. Porter
Keyword(s):  
Magnetic Susceptibility ◽  
High Resolution ◽  
Digital Camera ◽  
Dune Sand ◽  
Laptop Computer ◽  
Chinese Loess ◽  
Proxy Records ◽  
Eolian Sediments ◽  
Highly Correlated ◽  
Two Parameters

AbstractGrayscale intensity profiles from photographic images offer a rapid means of obtaining paleoclimate proxy records from Chinese loess, dune sand, and paleosols. Although the data can be obtained using conventional 35-mm film images, a digital camera and laptop computer will produce a high-resolution grayscale profile at a field site within minutes. Comparison of grayscale profiles with profiles of magnetic susceptibility measured down loess and dune-sand sections at sites on the Loess Plateau and Tibetan Plateau in a range of altitudes and climatic regimes shows that the two parameters are highly correlated. Therefore, grayscale intensity is a convenient alternative to magnetic susceptibility for generating paleoclimatic data in the loess and desert-margin regions of China. The resolution of both grayscale and susceptibility profiles ultimately is limited by bioturbation, which is most pronounced in paleosols.

scholarly journals A drone-based survey for large, basking freshwater turtle species

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0257720
Author(s):  
Amy P. Bogolin ◽  
Drew R. Davis ◽  
Richard J. Kline ◽  
Abdullah F. Rahman
Keyword(s):  
High Resolution ◽  
Sampling Methods ◽  
Digital Camera ◽  
Freshwater Turtle ◽  
Species Occurrence ◽  
Survey Tool ◽  
Turtle Species ◽  
Population Counts ◽  
Detailed Protocol

Conservation concerns are increasing for numerous freshwater turtle species, including Pseudemys gorzugi, which has led to a call for more research. However, traditional sampling methodologies are often time consuming, labor intensive, and invasive, restricting the amount of data that can be collected. Biases of traditional sampling methods can further impair the quality of the data collected, and these shortfalls may discourage their use. The use of unmanned aerial vehicles (UAVs, drones) for conducting wildlife surveys has recently demonstrated the potential to bridge gaps in data collection by offering a less labor intensive, minimally invasive, and more efficient process. Photographs and video can be obtained by camera attachments during a drone flight and analyzed to determine population counts, abundance, and other types of data. In this study we developed a detailed protocol to survey for large, freshwater turtle species in an arid, riverine landscape. This protocol was implemented with a DJI Matrice 600 Pro drone and a SONY ILCE α6000 digital camera to determine P. gorzugi and sympatric turtle species occurrence across 42 sites in southwestern Texas, USA. The use of a large drone and high-resolution camera resulted in high identification percentages, demonstrating the potential of drones to survey for large, freshwater turtle species. Numerous advantages to drone-based surveys were identified as well as some challenges, which were addressed with additional refinement of the protocol. Our data highlight the utility of drones for conducting freshwater turtle surveys and provide a guideline to those considering implementing drone-mounted high-resolution cameras as a survey tool.

scholarly journals ICT-based Science Education with High Resolution Digital Camera

2010 ◽  
Vol 30 (117) ◽  
pp. 20
Author(s):  
Fumiko Okiharu ◽  
Akizo Kobayashi
Keyword(s):  
Science Education ◽  
High Resolution ◽  
Digital Camera

scholarly journals Super-Resolution of Sentinel-2 Images at 10m Resolution without Reference Images

2021 ◽  
Author(s):  
Yunhe Li ◽  
Bo Li
Keyword(s):  
High Resolution ◽  
Image Quality Assessment ◽  
Kernel Estimation ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Reference Image ◽  
Optical Remote Sensing ◽  
Learning Technology ◽  
Reference Images ◽  
Sentinel 2

Sentinel-2 can provide multi-spectral optical remote sensing images in RGBN bands with a spatial resolution of 10m, but the spatial details provided are not enough for many applications. WorldView can provide HR multi-spectral images less than 2m, but it is a commercial paid resource with relatively high usage costs. In this paper, without any available reference images, Sentinel-2 images at 10m resolution are improved to a resolution of 2.5m through super-resolution (SR) based on deep learning technology. Our model, named DKN-SR-GAN, uses degradation kernel estimation and noise injection to construct a dataset of near-natural low-high-resolution (LHR) image pairs, with only low-resolution (LR) images and no high-resolution (HR) prior information. DKN-SR-GAN uses the Generative Adversarial Networks (GAN) combined of ESRGAN-type generator, PatchGAN-type discriminator and the VGG-19-type feature extractor, using perceptual loss to optimize the network, so as to obtain SR images with clearer details and better perceptual effects. Experiments demonstrate that in the quantitative comparison of the non-reference image quality assessment (NR-IQA) metrics like NIQE, BRISQUE and PIQE, as well as the intuitive visual effects of the generated images, compared with state-of-the-art models such as EDSR8-RGB, RCAN and RS-ESRGAN, our proposed model has obvious advantages.

scholarly journals A Digital Camera-Based Rotation-Invariant Fingerprint Verification Method

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Sajid Khan ◽  
Dong-Ho Lee ◽  
Asif Khan ◽  
Ahmad Waqas ◽  
Abdul Rehman Gilal ◽  
...  
Keyword(s):  
Feature Matching ◽  
Digital Camera ◽  
Reference Image ◽  
Digital Cameras ◽  
Scale Invariant ◽  
Image Capture ◽  
Verification Method ◽  
Reference Images ◽  
Binary Segmentation ◽  
The Difference

Fingerprint registration and verification is an active area of research in the field of image processing. Usually, fingerprints are obtained from sensors; however, there is recent interest in using images of fingers obtained from digital cameras instead of scanners. An unaddressed issue in the processing of fingerprints extracted from digital images is the angle of the finger during image capture. To match a fingerprint with 100% accuracy, the angles of the matching features should be similar. This paper proposes a rotation and scale-invariant decision-making method for the intelligent registration and recognition of fingerprints. A digital image of a finger is taken as the input and compared with a reference image for derotation. Derotation is performed by applying binary segmentation on both images, followed by the application of speeded up robust feature (SURF) extraction and then feature matching. Potential inliers are extracted from matched features by applying the M-estimator. Matched inlier points are used to form a homography matrix, the difference in the rotation angles of the finger in both the input and reference images is calculated, and finally, derotation is performed. Input fingerprint features are extracted and compared or stored based on the decision support system required for the situation.

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