Bio-inspired JPEG XR CODEC design for lossless HDR biomedical image

Shih, Yi-Shen; Zhang, Wen-Chih; Shen, Hsuan; Yang, Yi-Hsiang; Sun, Shung-Ting; Wu, Chi-Chang; Lee, Yaw-Chern; Lee, Sung-Shine; Huang, Sheng‐Chieh

doi:10.1109/compsym.2010.5685528

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…Note that this transform has the properties of the 1D structure in (7) and (8) since its transfer function is the same as that of the 'separable' transform in 2.2. In detail, the 1st lifting step predicts X 11 from multi-inputs X 00 , X 01 and X 10 (15) for (m)=(m 1 , m 2 ). In this prediction, a diagonal prediction As a result, this non-separable structure outputs the same band signals as the separable 2D transform apart from the rounding noise.…”

Section: Two-dimensional (2d) Wavelet Transformmentioning

confidence: 99%

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Non-Separable 3D Integer Wavelet Transform for Lossless Data Compression

Orachon¹

2014

CSSP

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This paper proposes a three-dimensional (3D) integer wavelet transform with reduced amount of rounding noise.Non-separable multi-dimensional lifting structures are introduced to decrease the total number of lifting steps. Since the lifting step contains a rounding operation, variance of the rounding noise generated due to the rounding operation inside the transform is reduced. This paper also investigates performance of the transform from various aspects such as 1) variance of the noise in frequency domain and those in pixel domain, 2) the rate distortion curve in lossy coding mode and the entropy rate in lossless coding mode, 3) computational time of the transforms, and 4) feature comparison with other methods. The proposed wavelet transform has a merit that its output signal, apart from the rounding noise, is exactly the same as the conventional separable structure which is a cascade of 1D structure. Due to this compatibility, it becomes possible to utilize legacy of previously designed 1D wavelet transforms with preferable properties such as the regularity. Furthermore, total amount of the rounding noise which is generated due to integer expression of signal values inside the transform is significantly reduced. This is because the total number of rounding operations is decreased by introducing the non-separable multi-dimensional lifting structure which includes multi-dimensional memory accessing. It contributes to increase coding performance of a system based on the 3D wavelet transform. As a result of experiments, it was observed that the proposed method increases performance of data compression of various 3D input signals.

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Section: Two-dimensional (2d) Wavelet Transformmentioning

confidence: 99%

“…It has been implemented in the lifting structure with rounding operations as the integer wavelet transform and extended based on the international standard [14,15]. The radar network has also been utilized for the reversible color transform and the integer DCT [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Non-Separable 3D Integer Wavelet Transform for Lossless Data Compression

Orachon¹

2014

CSSP

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“…The lossless coding of HDR images is especially important for storing and archiving original visual data such as medical, artistic, and astrograph images. Such data can be used for diagnosis based on medical images, analysis of astrograph images, art preservation, and bio-medical detections [17,18].…”

Section: Introductionmentioning

confidence: 99%

Bit-depth scalable lossless coding for high dynamic range images

Iwahashi

Yoshida

Mokhtar

et al. 2015

EURASIP J. Adv. Signal Process.

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In this paper, we propose a bit-depth scalable lossless coding method for high dynamic range (HDR) images based on a reversible logarithmic mapping. HDR images are generally expressed as floating-point data, such as in the OpenEXR or RGBE formats. Our bit-depth scalable coding approach outputs base layer data and enhancement layer data. It can reconstruct the low dynamic range (LDR) image from the base layer data and reconstructs the HDR image by adding the enhancement layer data. Most previous two-layer methods have focused on the lossy coding of HDR images. Unfortunately, the extension of previous lossy methods to lossless coding does not significantly compress the enhancement layer data. This is because the bit depth becomes very large, especially for HDR images in floating-point data format. To tackle this problem, we apply a reversible logarithmic mapping to the input HDR data. Moreover, we introduce a format conversion to avoid any degradation in the quality of the reconstructed LDR image. The proposed method is effective for both OpenEXR and RGBE formats. Through a series of experiments, we confirm that the proposed method decreases the volume of compressed data while maintaining the visual quality of the reconstructed LDR images.

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Bio-inspired JPEG XR CODEC design for lossless HDR biomedical image

Cited by 2 publications

References 6 publications

Non-Separable 3D Integer Wavelet Transform for Lossless Data Compression

Non-Separable 3D Integer Wavelet Transform for Lossless Data Compression

Bit-depth scalable lossless coding for high dynamic range images

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