&lt;title&gt;Low-bit-rate image compression evaluations&lt;/title&gt;

Brower, Bernard V.

doi:10.1117/12.179284

Cited by 7 publications

(4 citation statements)

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“…The results are shown in Tables 4 and 5, and in Figures 13 and 14. On Lena, the Chui-Lian multiwavelet outperformed both the D 4 and (3,5) scalar wavelets, while the GHM multiwavelet was comparable with D 4 and outperformed (3,5) at compression ratios of 32:1 and 64:1. The images in Figure 13 show that both the approximation-based multiwavelet schemes produce fewer Cartesian artifacts than the scalar wavelet, and the Chui-Lian multiwavelet preserves more detail (e.g.…”

Section: Transform-based Image Codingmentioning

confidence: 97%

“…A transformbased coder operates by transforming the data to remove redundancy, then quantizing the transform coefficients (a lossy step), and finally entropy coding the quantizer output. Because of their energy compaction properties and correspondence with the human visual system, wavelet representations have produced superior objective and subjective results in image compression [26,47,2,5]. Since a wavelet basis consists of functions with short support for high frequencies and long support for low frequencies, large smooth areas of an image may be represented with very few bits, and detail added where it is needed.…”

Section: Transform-based Image Codingmentioning

confidence: 99%

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The application of multiwavelet filterbanks to image processing

Strela

Heller

Strang

et al. 1999

IEEE Trans. on Image Process.

370

213

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Multiwavelets are a new addition to the body of wavelet theory. Realizable as matrix-valued filter banks leading to wavelet bases, multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible with scalar 2-channel wavelet systems. After reviewing this recently developed theory, we examine the use of multiwavelets in a filter bank setting for discrete-time signal and image processing. Multiwavelets differ from scalar wavelet systems in requiring two or more input streams to the multiwavelet filter bank. We describe two methods (repeated row and approximation/deapproximation) for obtaining such a vector input stream from a one-dimensional signal. Algorithms for symmetric extension of signals at boundaries are then developed, and naturally integrated with approximation-based preprocessing. We describe an additional algorithm for multiwavelet processing of two-dimensional signals, two rows at a time, and develop a new family of multiwavelets (the constrained pairs) that is well-suited to this approach. This suite of novel techniques is then applied to two basic signal processing problems, denoising via wavelet-shrinkage, and data compression. After developing the approach via model problems in one dimension, we applied multiwavelet processing to images, frequently obtaining performance superior to the comparable scalar wavelet transform.

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Section: Transform-based Image Codingmentioning

confidence: 97%

Section: Transform-based Image Codingmentioning

confidence: 99%

The application of multiwavelet filterbanks to image processing

Strela

Heller

Strang

et al. 1999

IEEE Trans. on Image Process.

370

213

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“…Wavelet transform ranked first in every case, while JPEG consistently ranked much lower. 12,13 This and other studies 14 strongly suggest the promise of the wavelet transform. …”

mentioning

confidence: 84%

Compressing and transmitting visible human images

Thoma

Long

1997

IEEE Multimedia

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challenging conventional storage, retrieval, and transmission methods. Here we discuss lossless and lossy methods to compress the images. We also consider advanced transmission-control protocol approaches plus a multisocket technique we developed for transmitting images over wide-area networks.T he National Library of Medicine's Visible Human Project acquired computerized tomography (CT), magnetic resonance imaging (MRI), and color cryosection images of a representative male and female cadaver to start building a digital image library of volumetric data. 1,2 These data sets serve as a common reference point for studying human anatomy, as a set of common public domain data for developing and testing medical imaging algorithms, and as a testbed and model for constructing image libraries accessible through networks. Researchers anticipate that this collection, particularly the color images, will become a data source for many multimedia applications. Examples include "fly through" instructional tutorials for human anatomy, biomechanical modeling software, visualization of lungs and bronchial tree anatomy, vascular anatomy visualization for realtime computation of catheter navigation and model-based surgery guidance, photorealistic volume-rendered anatomical atlases, interactive virtual dissection packages such as the Dissectable Human CD-ROM, an interactive 3D anatomic atlas published by the international health science publisher, Mosby, and many others. 3 More than 700 licensees in 26 countries already use the data sets for these purposes.The cryosection color images were taken by a charge-coupled device (CCD) scanner and captured as 70-mm photographs. In the male data set, 1,871 cross-sectional images exist for each modality, which amounts to about 15 Gbytes. The female data set, consisting of cross-sectional images taken at one-third the interval of the male, amounts to about 40 Gbytes, the total equaling 55 Gbytes. If we digitized the photographs at a resolution (4,096 by 2,700 pixels) exceeding that of the CCD scanner (2,048 by 1,216 pixels), this could deliver additional data to about 62 Gbytes total for the male and 173 Gbytes total for the female, for a combined total of 235 Gbytes.These 24-bits-per-pixel red, green, and blue (RGB) color image data offer the greatest challenges in storage and transmission. Their large sizes preclude rapid transfer over the Internet and distribution by CD-ROM or other optical media. (For example, even the CCD-captured set of 55 Gbytes requires 110 conventional CD-ROMs.) To alleviate this problem, we are investigating different compression techniques and communications methods.Specific research objectives include 1. Studying both lossy and lossless compression to reduce redundancy in the Visible Human color cryosection slice images and to select the most promising combination of parameters for each.2. Developing two compression methods, one lossy and the other lossless, using a combination of approaches. The development will include both compression and expansion software.3. St...

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“…There already have been many very successful works on image compression [11,14], and a large variety of algorithms have been proposed. A standard compression algorithm, JPEG, is available which will get good results on most images except when the compression ratio is high.…”

Section: Introductionmentioning

confidence: 99%

Improving Quality of Medical Image Reconstruction Using Wavelet Based Modified SPIHT Coding Technique

2013

IOSR-JDMS

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<title>Low-bit-rate image compression evaluations</title>

Cited by 7 publications

References 0 publications

The application of multiwavelet filterbanks to image processing

The application of multiwavelet filterbanks to image processing

Compressing and transmitting visible human images

Improving Quality of Medical Image Reconstruction Using Wavelet Based Modified SPIHT Coding Technique

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