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In this paper, we present a new tonemapping operator to display high dynamic range image onto conventional displayable devices and printers. In our work, a new tone map algorithm, derived from the Contrast Limited Adaptive histogram Equalization (CLAHE) technique is presented. Due to different luminance intervals could result in overlapped reaction on the limited response in limited response range...
Spatial resolution enhancement is usually required in the remote sensing field. Super-Resolution (SR) is a fusion process for reconstructing a High-Resolution (HR) image from several Low-Resolution (LR) images covering the same region in the world. It is difficult, however, for some satellite remote sensing arrangements to get several images of the same scene in a short time, especially for highly...
In this paper a new, faster approach which is different from all the other conventional image vectorization techniques. Using canny edge detection we are able to find the sharp edges in the image and the assigning shades to each identifiable segment using random colour extraction from the original image. Finally mapping the colour blobs with the SVG Schema and generating a scalable vector image. This...
As sensor networking technologies continue to develop, the notion of adding large-scale mobility into sensor networks is becoming feasible by crowd-sourcing data collection to personal mobile devices. However, tasking such networks at fine granularity becomes problematic because the sensors are heterogeneous and owned by users instead of network operators. In this paper, we present Zoom, a multi-resolution...
The CMOS image sensors are achieving a growing presence in today's mobile applications as the industry acknowledges the advances of the CMOS-based technology and its scaling possibilities. The roadmap recently unveiled for CMOS Image Sensor is announcing ever smaller pixels, after 1.4μm pixel pitch, demos with a pitch of 1.1μm were presented, and it also announces the future generation of pixels with...
Remote sensing imagery is an attractive source of land cover information. High resolution sensing imagery provides more land cover detail than low resolution sensing imagery. Due to more complex and noisier spectral signatures for the former, new algorithms are needed to deal with high resolution imagery. Based on an integration of spectral and spatial information, a novel classification method is...
High-resolution image collections pose unique challenges to analysts tasked with managing the associated data assets and deriving new information from them. While significant progress has been made towards rapid automated filtering, alignment, segmentation, characterization, and feature identification from image collections, the extraction of new insights still strongly depends on human intervention...
In this paper, we propose a novel image super-resolution algorithm, referred to as interpolation based on transductive regression with local and global consistency (TRLGC). Our algorithm first constructs a set of local interpolation models which can predict the intensity labels of all image samples, and a loss term will be minimized to keep the predicted labels of available low-resolution (LR) samples...
Microgrid imaging polarimeters consist of a focal plane array sensor with linear polarization filters of differing orientations overlaid at each pixel, similar in concept to the arrangement of spectral filters in a color CCD Bayer pattern camera. However, unlike spectral color cameras, microgrid systems use polarimetrically modulated intensity measurements to reconstruct the Stokes vector at each...
Image morphing has received much attention in recent years. It mainly involves feature specification, geometric transformation and color blending. Here, a novel calculation method of image morphing is proposed. First, a novel coordinate system called triangle coordinate system is defined, which has a great advantage in geometric transformation. Second, corresponding feature points on images are marked...
Digital compression of images, which is widely used to decrease the energy, time, and memory required for transmission and storage of video information, does not reduce the burden imposed on the analog-to-digital converters (A/Ds) employed for image quantization. Meanwhile this quantization is one of the most challenging problems in the design of large image sensors. Image quantization technique discussed...
We develop a new perspective invariant feature space representation of remotely sensed objects, regarding the features themselves as primitive observables of the 3D objects and to estimate them from multiple sensor measurements. This is formulated as an inverse problem in the feature coefficients. Once the coefficients are estimated they may be used to derive higher level features used by machine...
This research is attempted to estimate the biomass and leaf area index through identifying the cotton canopy and background pixels accurately. Cotton canopy was captured in different growth period of cotton by using an Olympus C740 Ultra Zoom digital camera. A protocol mixed hue of HLS color space with R, G value was setup and multiple judgment process was designed to extract cotton canopy pixels...
The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes...
This paper presents an immediate-mode, integrated approach to image fusion and visualization of multi-band satellite data, drawing from the computational resources of networked, high-resolution, tiled display environments. The presented workflow enables researchers to intuitively and interactively experiment with all tunable parameters, exposed through external devices such as MIDI controllers, to...
We propose an objective function to determine the focus step and the drift parameters for HRTEM images. Searching for the maximum value of this objective function, we can determine the focus step and the top-left coordinates of the images' corresponding region. Based on these optimized parameters, exit wave reconstruction can then be performed for experimental images. In this paper, we focus on the...
It is well known that the noise in magnetic resonance (MR) magnitude images obeys a Rician distribution. Denoising of MR images is of importance for clinical diagnosis and computerized analysis, such as tissue classification, segmentation, and registration. We propose a post-acquisition denoising algorithm in an attempt to automatically remove the random fluctuations and bias introduced by Rician...
We report the implementation of a fully on-chip, lensless, sub-pixel resolving optofluidic microscope (SROFM) based on the super resolution algorithm. The device utilizes microfluidic flow to deliver specimens directly across a complementary metal oxide semiconductor (CMOS) sensor to generate a sequence of low-resolution (LR) projection images, where resolution is limited by the sensor's pixel size...
Knife Edge Scanning Microscopy (KESM) is a high-throughput imaging technique used to obtain large-scale anatomical information (≈1cm3) at sub-micrometer resolution. Data acquisition has been fully automated, however significant post-processing and reconstruction must be done manually. KESM is unique in that illumination and tissue sectioning are performed using a diamond knife. Therefore many of the...
Plaque composition analysis is a critical tool in identifying vulnerable atherosclerotic plaques. Intravascular ultrasound with spectral analysis of the backscattered radio frequency (RF) signals (IVUS-VH) is currently considered as the gold standard for the evaluation of coronary plaque composition, while CT coronary angiography (CTA) has been proposed as a potential non-invasive counterpart. In...
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