18,677 research outputs found
Optimized kernel minimum noise fraction transformation for hyperspectral image classification
This paper presents an optimized kernel minimum noise fraction transformation (OKMNF) for feature extraction of hyperspectral imagery. The proposed approach is based on the kernel minimum noise fraction (KMNF) transformation, which is a nonlinear dimensionality reduction method. KMNF can map the original data into a higher dimensional feature space and provide a small number of quality features for classification and some other post processing. Noise estimation is an important component in KMNF. It is often estimated based on a strong relationship between adjacent pixels. However, hyperspectral images have limited spatial resolution and usually have a large number of mixed pixels, which make the spatial information less reliable for noise estimation. It is the main reason that KMNF generally shows unstable performance in feature extraction for classification. To overcome this problem, this paper exploits the use of a more accurate noise estimation method to improve KMNF. We propose two new noise estimation methods accurately. Moreover, we also propose a framework to improve noise estimation, where both spectral and spatial de-correlation are exploited. Experimental results, conducted using a variety of hyperspectral images, indicate that the proposed OKMNF is superior to some other related dimensionality reduction methods in most cases. Compared to the conventional KMNF, the proposed OKMNF benefits significant improvements in overall classification accuracy
Hydrographic charting from LANDSAT Satellite: A comparison with aircraft imagery
The relative capabilities of two remote-sensing systems in measuring depth and, consequently, bottom contours in sandy-bottomed and sediment-laden coastal waters were determined quantitatively. The multispectral scanner (MSS), orbited on the LANDSAT-2 Satellite, and the ocean color scanner (OCS), flown on U-2 aircraft, were used. Analysis of imagery taken simultaneously indicates a potential for hydrographic charting of marine coastal and shallow shelf areas, even when water turbidity is a factor. Several of the eight optical channels examined on the OCS were found to be sensitive to depth or depth-related information. The greatest sensitivity was in OCS-4(0.544 + or - 0.012 microns) from which contours corresponding to depths up to 12m were determined. The sharpness of these contours and their spatial stability through time suggests that upwelling radiance is a measure of bottom reflectance and not of water turbidity. The two visible channels on LANDSAT's MSS were less sensitive in the discrimination of contours, with depths up to 8m in the high-gain mode (3x) determined in MSS-4(0.5 to 0.6 microns)
Signal processing methodologies for an acoustic fetal heart rate monitor
Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use
Development, implementation and evaluation of satellite-aided agricultural monitoring systems
Research supporting the use of remote sensing for inventory and assessment of agricultural commodities is summarized. Three task areas are described: (1) corn and soybean crop spectral/temporal signature characterization; (2) efficient area estimation technology development; and (3) advanced satellite and sensor system definition. Studies include an assessment of alternative green measures from MSS variables; the evaluation of alternative methods for identifying, labeling or classification targets in an automobile procedural context; a comparison of MSS, the advanced very high resolution radiometer and the coastal zone color scanner, as well as a critical assessment of thematic mapper dimensionally and spectral structure
Natural images from the birthplace of the human eye
Here we introduce a database of calibrated natural images publicly available
through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we
acquired about 5000 six-megapixel images of Okavango Delta of Botswana, a
tropical savanna habitat similar to where the human eye is thought to have
evolved. Some sequences of images were captured unsystematically while
following a baboon troop, while others were designed to vary a single parameter
such as aperture, object distance, time of day or position on the horizon.
Images are available in the raw RGB format and in grayscale. Images are also
available in units relevant to the physiology of human cone photoreceptors,
where pixel values represent the expected number of photoisomerizations per
second for cones sensitive to long (L), medium (M) and short (S) wavelengths.
This database is distributed under a Creative Commons Attribution-Noncommercial
Unported license to facilitate research in computer vision, psychophysics of
perception, and visual neuroscience.Comment: Submitted to PLoS ON
Study of First-Order Thermal Sigma-Delta Architecture for Convective Accelerometers
This paper presents the study of an original closed-loop conditioning
approach for fully-integrated convective inertial sensors. The method is
applied to an accelerometer manufactured on a standard CMOS technology using an
auto-aligned bulk etching step. Using the thermal behavior of the sensor as a
summing function, a first order sigma-delta modulator is built. This
"electro-physical" modulator realizes an analog-to-digital conversion of the
signal. Besides the feedback scheme should improve the sensor performance.Comment: Submitted on behalf of EDA Publishing Association
(http://irevues.inist.fr/handle/2042/16838
Quality criteria benchmark for hyperspectral imagery
Hyperspectral data appear to be of a growing interest
over the past few years. However, applications for hyperspectral
data are still in their infancy as handling the significant size of
the data presents a challenge for the user community. Efficient
compression techniques are required, and lossy compression,
specifically, will have a role to play, provided its impact on remote
sensing applications remains insignificant. To assess the data
quality, suitable distortion measures relevant to end-user applications
are required. Quality criteria are also of a major interest
for the conception and development of new sensors to define their
requirements and specifications. This paper proposes a method to
evaluate quality criteria in the context of hyperspectral images.
The purpose is to provide quality criteria relevant to the impact
of degradations on several classification applications. Different
quality criteria are considered. Some are traditionnally used in
image and video coding and are adapted here to hyperspectral
images. Others are specific to hyperspectral data.We also propose
the adaptation of two advanced criteria in the presence of different
simulated degradations on AVIRIS hyperspectral images. Finally,
five criteria are selected to give an accurate representation of the
nature and the level of the degradation affecting hyperspectral
data
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