1,032 research outputs found
Historical forest biomass dynamics modelled with Landsat spectral trajectories
Acknowledgements National Forest Inventory data are available online, provided by Ministerio de Agricultura, Alimentación y Medio Ambiente (España). Landsat images are available online, provided by the USGS.Peer reviewedPostprin
Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment
Processing of digital images is continuously gaining in volume and relevance,
with concomitant demands on data storage, transmission and processing power.
Encoding the image information in quantum-mechanical systems instead of
classical ones and replacing classical with quantum information processing may
alleviate some of these challenges. By encoding and processing the image
information in quantum-mechanical systems, we here demonstrate the framework of
quantum image processing, where a pure quantum state encodes the image
information: we encode the pixel values in the probability amplitudes and the
pixel positions in the computational basis states. Our quantum image
representation reduces the required number of qubits compared to existing
implementations, and we present image processing algorithms that provide
exponential speed-up over their classical counterparts. For the commonly used
task of detecting the edge of an image, we propose and implement a quantum
algorithm that completes the task with only one single-qubit operation,
independent of the size of the image. This demonstrates the potential of
quantum image processing for highly efficient image and video processing in the
big data era.Comment: 13 pages, including 9 figures and 5 appendixe
Astronomical image manipulation in the transform domain
It is well known that images are usually stored and transmitted in the compressed form to save memory space and I/O bandwidth. Among many image compression schemes, transform coding is a widely used coding method. Traditionally, processing a compressed image requires decompression first. Following manipulations, the processed image is compressed again for storage. To reduce the computational complexity and processing time, manipulating images in the semi-compressed or transform domain is an efficient solution; Many astronomical images are compressed and stored by JPEG and HCOM-PRESS, which are based on the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT), respectively. In this thesis, a suite of image processing algorithms in the transform domain, DCT and DWT, is developed. In particular, new methods for edge enhancement and minimum (MIN)/maximum (MAX) gray scale intensity estimation in the DCT domain are proposed. Algebraic operations and image interpolation in the DWT domain are addressed. The superiority of new algorithms over the conventional ones is demonstrated by comparing the time complexities and qualities of the processed image in the transform domain to those in the spatial domain
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