Results 1  10
of
7,552
The Laplacian Pyramid as a Compact Image Code
, 1983
"... We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixeltopixel correlations a ..."
Abstract

Cited by 1388 (12 self)
 Add to MetaCart
We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixeltopixel correlations
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
Abstract

Cited by 1513 (20 self)
 Add to MetaCart
Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear
PCASIFT: A more distinctive representation for local image descriptors
, 2004
"... Stable local feature detection and representation is a fundamental component of many image registration and object recognition algorithms. Mikolajczyk and Schmid [14] recently evaluated a variety of approaches and identified the SIFT [11] algorithm as being the most resistant to common image deforma ..."
Abstract

Cited by 591 (6 self)
 Add to MetaCart
deformations. This paper examines (and improves upon) the local image descriptor used by SIFT. Like SIFT, our descriptors encode the salient aspects of the image gradient in the feature point's neighborhood; however, instead of using SIFT's smoothed weighted histograms, we apply Principal Components
Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging
 MAGNETIC RESONANCE IN MEDICINE 58:1182–1195
, 2007
"... The sparsity which is implicit in MR images is exploited to significantly undersample kspace. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain–for example, in terms of spatial finit ..."
Abstract

Cited by 538 (11 self)
 Add to MetaCart
undersampling schemes are developed and analyzed by means of their aliasing interference. Incoherence is introduced by pseudorandom variabledensity undersampling of phaseencodes. The reconstruction is performed by minimizing the ℓ1 norm of a transformed image, subject to data fidelity constraints. Examples
A volumetric method for building complex models from range images,”
 in Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. ACM,
, 1996
"... Abstract A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: incremental updating, representation of directional uncertainty, the ability to fill gaps in the reconstruction, ..."
Abstract

Cited by 1020 (17 self)
 Add to MetaCart
with one range image at a time, we first scanconvert it to a distance function, then combine this with the data already acquired using a simple additive scheme. To achieve space efficiency, we employ a runlength encoding of the volume. To achieve time efficiency, we resample the range image to align
Original Image Encoded Image
"... eurons, each with L synapses. Let W y be an appropriately selected output weight matrix. Pass all N hidden vectors, h(n), representing an encoded image, H , through the output layer to obtain the output signal, y(n). Reassemble the output signals into p = r c image blocks to obtain a reconstru ..."
Abstract
 Add to MetaCart
eurons, each with L synapses. Let W y be an appropriately selected output weight matrix. Pass all N hidden vectors, h(n), representing an encoded image, H , through the output layer to obtain the output signal, y(n). Reassemble the output signals into p = r c image blocks to obtain a re
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
Abstract

Cited by 639 (15 self)
 Add to MetaCart
that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported
Inpainting Through Fractal Image Encoding by
"... Abstract. Computational techniques that attempt to reconstruct missing pixels in an image are broadly referred to as digital image inpainting. Approaches have been developed based on continuation of isophotes, curvaturedriven diffusion, as well as approaches that require decomposing the image into, ..."
Abstract
 Add to MetaCart
, for example, cartoon (smooth) and texture parts. The purpose of this paper is to propose a novel approach to inpainting based on fractal image encoding. The basic idea is to exploit self similarity in the image using fractal image encoding schemes. A modification of the encoding algorithm is needed to take
Fast Fractal Image Encoder
"... Although fractal image compression can achieve high compression ratio theoretically, it needs a lot of encoding time to encode an image so that it has not been widely applied as other coding schemes in the field of image compression. In this paper, an algorithm is devised to improve this drawback. T ..."
Abstract
 Add to MetaCart
Although fractal image compression can achieve high compression ratio theoretically, it needs a lot of encoding time to encode an image so that it has not been widely applied as other coding schemes in the field of image compression. In this paper, an algorithm is devised to improve this drawback
Image Encoding, Data
, 1997
"... The World Wide Web has rapidly become the hot new mass communications medium. Content creators are using similar design and layout styles as in printed magazines, i.e., with many color images and graphics. The information is transmitted over plain telephone lines, where the speed/ price tradeoff is ..."
Abstract
 Add to MetaCart
off is much more severe than in the case of printed media. The standard design approach is to use palettized color and to limit as much as possible the number of colors used, so that the images can be encoded with a small number of bits per pixel using the Graphics Interchange Format (GIF) file format
Results 1  10
of
7,552