Lossless compression of segmented biomedical images with an adaptive arithmetic coding model

Zamora, Gilberto; Mitra, Sunanda

doi:10.1109/cbms.1999.781270

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…In our implementation wavelet transform using Daub 4 has been applied following lifting factorization [1] with a fixed scaling factor. Finally, adaptive arithmetic coding [3,4] has been used for each subimage of the wavelet decomposed and integer to integer mapped images prior to archiving and transmission.…”

Section: Introductionmentioning

confidence: 99%

Segmentation by color space transformation prior to lifting and integer wavelet transformation for efficient lossless coding and transmission

Zamora

Yang²,

Wilson³

et al.

4th IEEE Southwest Symposium on Image Analysis and Interpretation

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Efficient lossless coding and transmission of large color images through bandlimited channels are of growing interests in many applications. Classically lossless coding is performed in the spatial domain by entropy coding of the decorrelated pixels. However, such coding yields only a maximum of 3:1 compression. Recent developments in integer to integer wavelet transform allow multiresolution representation and progressive transmission of images through bandlimited channels starting from the entropy coded lowest resolution image. However, such schemes are able to reduce the bit rate to a limited extent. We present here an efficient automated technique using a simple color space transformation from RGB to HSI that segments and retrieves the color object contour in a fast manner. When such segmented image is subjected to integer to integer wavelet transform followed by an adaptive arithmetic coding model, lossless compression up to 20:1 has been achieved for some color images. Due to the substantial decrease in size of the input image to be processed, the execution time of the entire algorithm is reduced drastically. Although color transformation from RGB to L * a * b * results in better visual appearance as well as more compressibility, this nonlinear transformation is more computationally intensive. Therefore for progressive transmission a simple color transformation scheme is preferable.

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Section: Introductionmentioning

confidence: 99%

Segmentation by color space transformation prior to lifting and integer wavelet transformation for efficient lossless coding and transmission

Zamora

Yang²,

Wilson³

et al.

4th IEEE Southwest Symposium on Image Analysis and Interpretation

Self Cite

View full text Add to dashboard Cite

show abstract

Efficient visualization of encoded Fourier transform infrared microscopic data of osteoporotic bone

Zamora

Yang

Mitra

et al.

Proceedings 14th IEEE Symposium on Computer-Based Medical Systems. CBMS 2001

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<title>Efficient lossless coding model for medical images by applying integer-to-integer wavelet transform to segmented images</title>

Yang¹,

Zamora²,

Wilson³

et al. 2000

SPIE Proceedings

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Existing lossless coding models yield only up to 3 : 1 compression. However, a much higher lossless compression can be achieved for certain medical images when the images are segmented prior to applying integer to integer wavelet transform and lossless coding. The methodology used in this research work is to apply a contour detection scheme to segment the image first. The segmented image is then wavelet transformed with integer to integer mapping to obtain a lower weighted entropy than the original. An adaptive arithmetic model is then applied to code the transformed image losslessly. For the male visible human color image set, the overall average lossless compression using the above scheme is around 10: 1 whereas the compression ratio of an individual slice can be as high as 1 6: 1 . The achievable compression ratio depends on the actual bit rate of the segmented images attained by lossless coding as well as the compression obtainable from segmentation alone. The computational time required by the entire process is fast enough for application on large medical images.

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Lossless compression of segmented biomedical images with an adaptive arithmetic coding model

Cited by 3 publications

References 4 publications

Segmentation by color space transformation prior to lifting and integer wavelet transformation for efficient lossless coding and transmission

Segmentation by color space transformation prior to lifting and integer wavelet transformation for efficient lossless coding and transmission

Efficient visualization of encoded Fourier transform infrared microscopic data of osteoporotic bone

<title>Efficient lossless coding model for medical images by applying integer-to-integer wavelet transform to segmented images</title>

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