Results 271 to 280 of about 207,274 (314)
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SPIE Proceedings, 1989
High spectral and high spatial resolution images will be performed on-board satellites using a new instrument called a Fourier transform spectro-imager. Based on the principle of the Michelson interferometer, this instrument will give images in which each pixel is the whole spectrum of the observed point on Earth.
C Mailhes, P Vermande, F Castanie
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High spectral and high spatial resolution images will be performed on-board satellites using a new instrument called a Fourier transform spectro-imager. Based on the principle of the Michelson interferometer, this instrument will give images in which each pixel is the whole spectrum of the observed point on Earth.
C Mailhes, P Vermande, F Castanie
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Fractals, 1994
This paper begins by presenting a simple explanation of the main ideas in fractal image compression. It then presents a brief discussion of the current state of the art along with some results comparing fractal encoding, JPEG, and a wavelet scheme. The conclusion contains references to many of the latest theoretical and implementation results.
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This paper begins by presenting a simple explanation of the main ideas in fractal image compression. It then presents a brief discussion of the current state of the art along with some results comparing fractal encoding, JPEG, and a wavelet scheme. The conclusion contains references to many of the latest theoretical and implementation results.
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An Architecture for Compressive Imaging
2006 International Conference on Image Processing, 2006Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for reconstruction and processing. In this paper, we propose algorithms and hardware to support a new theory of Compressive Imaging.
Michael B. Wakin +7 more
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Multispectral image compression
Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002Image compression has been one of the mainstream research topics in image processing. The research usually focuses on compressing images that are visible to humans. Images are usually gray-level images or RGB color images. Advances in technology enable one to make the detailed processing of spectral color features in the images.
Arto Kaarna +3 more
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Journal of Electronic Imaging, 2014
We propose an algorithm to recover the latent image from the blurred and compressed input. In recent years, although many image deblurring algorithms have been proposed, most of the previous methods do not consider the compression effect in blurry images. Actually, it is unavoidable in practice that most of the real-world images are compressed.
Yuquan Xu, Xiyuan Hu, Silong Peng
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We propose an algorithm to recover the latent image from the blurred and compressed input. In recent years, although many image deblurring algorithms have been proposed, most of the previous methods do not consider the compression effect in blurry images. Actually, it is unavoidable in practice that most of the real-world images are compressed.
Yuquan Xu, Xiyuan Hu, Silong Peng
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Journal of Functional Programming, 2013
Abstract This paper describes some experiences of using fractal image compression as the subject of an assignment for a functional programming course using Haskell. The students were fascinated by the reproduction of images from their encodings and engaged well with the exercise which involved only elementary functional programming ...
C. E. Martin, S. A. Curtis
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Abstract This paper describes some experiences of using fractal image compression as the subject of an assignment for a functional programming course using Haskell. The students were fascinated by the reproduction of images from their encodings and engaged well with the exercise which involved only elementary functional programming ...
C. E. Martin, S. A. Curtis
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SPIE Proceedings, 2005
Most consumer-level digital cameras use a color filter array to capture color mosaic data followed by demosaicking to obtain full-color images. However, many sophisticated demosaicking algorithms are too complex to implement on-board a camera. To use these algorithms, one must transfer the mosaic data from the camera to a computer without introducing ...
Kapil A. Chaudhari, Stanley J. Reeves
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Most consumer-level digital cameras use a color filter array to capture color mosaic data followed by demosaicking to obtain full-color images. However, many sophisticated demosaicking algorithms are too complex to implement on-board a camera. To use these algorithms, one must transfer the mosaic data from the camera to a computer without introducing ...
Kapil A. Chaudhari, Stanley J. Reeves
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Image registration by compression
Information Sciences, 2010Abstract Image registration consists in finding the transformation that brings one image into the best possible spatial correspondence with another image. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can ...
Anton Bardera +3 more
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Compression of sequential images
Proceedings 12th IEEE Symposium on Computer-Based Medical Systems (Cat. No.99CB36365), 2003We consider compressing sequential images (i.e., images with a strong correlation which are not time-dependent, such as proximal MR/CT slices or the image dataset from the visible human project) using neural nets. The basic idea is that compression takes place in the encoding of the outputs of the hidden layer, which is then transmitted to the receiver.
Mohamed A. Kerasha, Ian R. Greenshields
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Journal of Visual Communication and Image Representation, 1993
Abstract This paper deals with a number of issues which can ultimately be used for development of effective algorithms for lossless compression of digitized images. The issues discussed are: (1) What are the different types of entropies? (2) How effective are the existing compression algorithms as compared to the entropy of images?
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Abstract This paper deals with a number of issues which can ultimately be used for development of effective algorithms for lossless compression of digitized images. The issues discussed are: (1) What are the different types of entropies? (2) How effective are the existing compression algorithms as compared to the entropy of images?
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